ComparaR
Pedro González
2024-04-11
pacman::p_load(pacman,dplyr,GGally,ggplot2,ggthemes,ggvis,httr,lubridate,plotly,rio,rmarkdown,shiny,stringr,tidyr,tidyverse,lattice,caret,pls,MASS,yarrr,psych,ggcorrplot,GGally,CCA,CCP,rpart,rpart.plot)library(tidyverse)
library(rpart)
library(rpart.plot)
library(caret)
library(car)## Loading required package: carData##
## Attaching package: 'car'## The following object is masked from 'package:psych':
##
## logit## The following object is masked from 'package:purrr':
##
## some## The following object is masked from 'package:dplyr':
##
## recodelibrary(stats)library("rio")Generación de los datos
A partir de las 16 análisis de las muestras en la columna polar, se generaron 8 “réplicas” de cada análisis añadiendo un ruido blanco calculado con la función rnorm(n,mean=0,sd=1)0.01valores de tal manera que se generen pequeñas variaciones a los mismos.
Al final tenemos un juego de 144 filas=8*16+16
Estos datos se guardaron en el excel=CCADatosTest.xlsx
mm0<-import("PolarCorrelation.xlsx")
mm0<-mm0 %>% mutate(Total=Aroma+Flavor+Aftertaste+Acidity+Body+Balance+Overall+30)
nombres=names(mm0[,1:86])
codigo=c(gsub(" ","",paste("A",1:86)))
names(mm0)<-c(gsub(" ","",paste("A",1:86)),"Aroma","Flavor","Aftertaste","Acidity","Body","Balance","Overall","Total")mm1<-import("CCADatos03.csv")
mm1<-mm1 %>% mutate(Total=Aroma+Flavor+Aftertaste+Acidity+Body+Balance+Overall+30)
#mm<-mm1[,1:87]
#mm["Aroma"]<-round(atributo,1)
mm1<-mm1[,-87]
mm1<-mm1[,-87]
mm1<-mm1[,-87]
mm1<-mm1[,-87]
mm1<-mm1[,-87]
mm1<-mm1[,-87]
mm<-mm1[,-87]
d<-(max(mm$Total)-min(mm$Total))/4
d1<-min(mm$Total)+d
d2<-min(mm$Total)+d*2
d3<-min(mm$Total)+d*3
breakpoints=seq(min(mm$Total),max(mm$Total),d)
breakpoints<-c(-Inf, d1, d2,d3, Inf)
classified<-cut(mm$Total,breaks=breakpoints,labels=c("Bajo","Medio","Alto","Excelente"))
mm$Total<-factor(classified)
varNames=names(mm)[1:86]Clasificación de las muestras usando el algoritmo de Arbol de decisión
vv<-rep(0,86)
## Se realizaran 100 corridas del algoritmo
nt=0
vx2=""
for(i in 1:100){
print(paste0("CORRIDA ",i))
training2 <- sample_frac(mm, .7) ## conjunto de entrenamiento 70% de las muestras escogidas al azar
test2 <- setdiff(mm, training2) ## Conjunto de prueba, el remanente de las muestras
arbol_2 <- rpart(formula = Total ~ ., data = training2,control = rpart.control(cp = 0.025, xval = 35, minsplit = 5))
prediccion_2 <- predict(arbol_2, newdata = test2, type = "class" )
rpart.plot(arbol_2)
# Cálculo de la matriz de confusión
c<-confusionMatrix(prediccion_2, test2[["Total"]])
print(c)
# Nombre de las variables utilizadas en el el árbol de decisión
v<-arbol_2$frame$var[arbol_2$frame$var != "<leaf>"]
for(vx in v){
n<-which(varNames==vx)
vv[n]=vv[n]+1
}
print(paste0("VARIABLES:",paste(v,collapse=",")))
new_string <- paste(v, collapse = "+")
df2<-data.frame(Total=test2$Total,pred=prediccion_2)
f<-paste0("Total~",new_string) %>% as.formula #Calcula fórmula de regresión
metodo<-lm(f,data=mm0)
#summary(metodo)
plot(metodo$fitted.values,mm0$Total,xlim=c(86,90),ylim=c(86,90),main=paste0("VARIABLES:",paste(v,collapse=",")))
abline(0,1,col="blue")
print(summary(metodo))
a<-vif(metodo)
print(a)
aa=summary(metodo)
n<-aa$coefficients[,4]<0.05
nx<-sum(n)
if(nx>nt){
nt=nx
vx2=new_string
}
print("--------------------------------------------------------------------------------------")
}## [1] "CORRIDA 1"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 3 0 0
## Medio 8 46 10 2
## Alto 0 0 100 19
## Excelente 0 0 16 113
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7525
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9388 0.7937 0.8433
## Specificity 0.99029 0.9315 0.9116 0.9227
## Pos Pred Value 0.88889 0.6970 0.8403 0.8760
## Neg Pred Value 0.97452 0.9891 0.8829 0.9009
## Prevalence 0.09384 0.1437 0.3695 0.3930
## Detection Rate 0.07038 0.1349 0.2933 0.3314
## Detection Prevalence 0.07918 0.1935 0.3490 0.3783
## Balanced Accuracy 0.87015 0.9351 0.8526 0.8830
## [1] "VARIABLES:A7,A64,A37,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68202 -0.29794 -0.00586 0.40977 0.80494
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.4351 1.0529 81.144 < 2e-16 ***
## A7 30.0093 7.1476 4.198 0.00149 **
## A64 -0.2288 0.2174 -1.052 0.31532
## A37 -10.3675 5.4328 -1.908 0.08278 .
## A9 0.5632 3.7960 0.148 0.88474
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5362 on 11 degrees of freedom
## Multiple R-squared: 0.7542, Adjusted R-squared: 0.6648
## F-statistic: 8.438 on 4 and 11 DF, p-value: 0.00229
##
## A7 A64 A37 A9
## 1.132883 1.326347 1.493141 1.598844
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 2"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 4 0 0
## Medio 7 39 8 0
## Alto 0 5 115 21
## Excelente 0 0 9 115
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7629
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.72000 0.8125 0.8712 0.8456
## Specificity 0.98734 0.9488 0.8756 0.9561
## Pos Pred Value 0.81818 0.7222 0.8156 0.9274
## Neg Pred Value 0.97806 0.9686 0.9150 0.9032
## Prevalence 0.07331 0.1408 0.3871 0.3988
## Detection Rate 0.05279 0.1144 0.3372 0.3372
## Detection Prevalence 0.06452 0.1584 0.4135 0.3636
## Balanced Accuracy 0.85367 0.8807 0.8734 0.9008
## [1] "VARIABLES:A7,A7,A36,A10,A83"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81901 -0.25377 -0.01265 0.40684 0.62531
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.626 1.489 58.176 4.78e-15 ***
## A7 18.549 9.884 1.877 0.0873 .
## A36 -1.861 0.863 -2.156 0.0541 .
## A10 2.953 1.823 1.619 0.1337
## A83 1.208 0.907 1.332 0.2099
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5449 on 11 degrees of freedom
## Multiple R-squared: 0.7462, Adjusted R-squared: 0.6539
## F-statistic: 8.084 on 4 and 11 DF, p-value: 0.002709
##
## A7 A36 A10 A83
## 2.097768 1.841519 1.500973 1.323961
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 3"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 3 0 0
## Medio 6 41 13 0
## Alto 0 0 103 16
## Excelente 0 0 16 121
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7653
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78571 0.9318 0.7803 0.8832
## Specificity 0.99042 0.9360 0.9234 0.9216
## Pos Pred Value 0.88000 0.6833 0.8655 0.8832
## Neg Pred Value 0.98101 0.9893 0.8694 0.9216
## Prevalence 0.08211 0.1290 0.3871 0.4018
## Detection Rate 0.06452 0.1202 0.3021 0.3548
## Detection Prevalence 0.07331 0.1760 0.3490 0.4018
## Balanced Accuracy 0.88806 0.9339 0.8519 0.9024
## [1] "VARIABLES:A7,A64,A7,A64"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.11047 -0.49778 0.07139 0.42803 0.71293
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.8366 1.0455 81.141 < 2e-16 ***
## A7 31.4398 7.8213 4.020 0.00146 **
## A64 -0.2916 0.2199 -1.326 0.20763
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5922 on 13 degrees of freedom
## Multiple R-squared: 0.6457, Adjusted R-squared: 0.5912
## F-statistic: 11.85 on 2 and 13 DF, p-value: 0.001177
##
## A7 A64
## 1.112161 1.112161
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 4"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 2 0 2
## Medio 7 32 16 0
## Alto 0 0 122 12
## Excelente 0 0 17 110
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4545
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7526
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.94118 0.7871 0.8871
## Specificity 0.98722 0.92508 0.9355 0.9217
## Pos Pred Value 0.84000 0.58182 0.9104 0.8661
## Neg Pred Value 0.97785 0.99301 0.8406 0.9346
## Prevalence 0.08211 0.09971 0.4545 0.3636
## Detection Rate 0.06158 0.09384 0.3578 0.3226
## Detection Prevalence 0.07331 0.16129 0.3930 0.3724
## Balanced Accuracy 0.86861 0.93313 0.8613 0.9044
## [1] "VARIABLES:A7,A64,A80,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7593 -0.4354 0.1194 0.4229 0.7851
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.9383 1.2161 69.844 6.44e-16 ***
## A7 31.9706 7.7898 4.104 0.00175 **
## A64 -0.3179 0.2302 -1.381 0.19476
## A80 0.6079 0.5718 1.063 0.31050
## A9 -2.8645 3.5101 -0.816 0.43177
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5891 on 11 degrees of freedom
## Multiple R-squared: 0.7033, Adjusted R-squared: 0.5954
## F-statistic: 6.519 on 4 and 11 DF, p-value: 0.006095
##
## A7 A64 A80 A9
## 1.114783 1.232018 1.039607 1.132566
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 5"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 7 0 0
## Medio 6 35 13 0
## Alto 0 7 98 21
## Excelente 0 0 11 118
##
## Overall Statistics
##
## Accuracy : 0.8094
## 95% CI : (0.7636, 0.8497)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7206
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80645 0.7143 0.8033 0.8489
## Specificity 0.97742 0.9349 0.8721 0.9455
## Pos Pred Value 0.78125 0.6481 0.7778 0.9147
## Neg Pred Value 0.98058 0.9512 0.8884 0.9009
## Prevalence 0.09091 0.1437 0.3578 0.4076
## Detection Rate 0.07331 0.1026 0.2874 0.3460
## Detection Prevalence 0.09384 0.1584 0.3695 0.3783
## Balanced Accuracy 0.89194 0.8246 0.8377 0.8972
## [1] "VARIABLES:A7,A64,A25,A25,A28"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73514 -0.21874 0.00616 0.24276 0.55420
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.5748 1.3357 67.062 1.01e-15 ***
## A7 26.4666 5.4432 4.862 0.000501 ***
## A64 -0.4068 0.1626 -2.502 0.029380 *
## A25 -1.4123 0.3740 -3.776 0.003068 **
## A28 0.9736 2.1359 0.456 0.657385
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3989 on 11 degrees of freedom
## Multiple R-squared: 0.8639, Adjusted R-squared: 0.8145
## F-statistic: 17.46 on 4 and 11 DF, p-value: 9.891e-05
##
## A7 A64 A25 A28
## 1.186940 1.339418 1.512179 1.689927
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 6"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 1 0 0
## Medio 10 47 11 0
## Alto 0 0 100 16
## Excelente 0 0 15 118
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7735
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.69697 0.9792 0.7937 0.8806
## Specificity 0.99675 0.9283 0.9256 0.9275
## Pos Pred Value 0.95833 0.6912 0.8621 0.8872
## Neg Pred Value 0.96845 0.9963 0.8844 0.9231
## Prevalence 0.09677 0.1408 0.3695 0.3930
## Detection Rate 0.06745 0.1378 0.2933 0.3460
## Detection Prevalence 0.07038 0.1994 0.3402 0.3900
## Balanced Accuracy 0.84686 0.9537 0.8596 0.9041
## [1] "VARIABLES:A7,A64,A6,A3"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0877 -0.3075 0.1048 0.3268 0.7264
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.9164 1.0132 83.812 < 2e-16 ***
## A7 33.5700 8.8755 3.782 0.00303 **
## A64 -0.3936 0.2400 -1.640 0.12918
## A6 -0.4575 0.2635 -1.736 0.11037
## A3 1.9077 3.4569 0.552 0.59209
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5699 on 11 degrees of freedom
## Multiple R-squared: 0.7224, Adjusted R-squared: 0.6214
## F-statistic: 7.155 on 4 and 11 DF, p-value: 0.004323
##
## A7 A64 A6 A3
## 1.546438 1.430241 1.394996 1.708379
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 7"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 3 0 0
## Medio 3 44 17 0
## Alto 0 0 104 18
## Excelente 0 0 14 112
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7643
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.89655 0.9362 0.7704 0.8615
## Specificity 0.99038 0.9320 0.9126 0.9336
## Pos Pred Value 0.89655 0.6875 0.8525 0.8889
## Neg Pred Value 0.99038 0.9892 0.8584 0.9163
## Prevalence 0.08504 0.1378 0.3959 0.3812
## Detection Rate 0.07625 0.1290 0.3050 0.3284
## Detection Prevalence 0.08504 0.1877 0.3578 0.3695
## Balanced Accuracy 0.94347 0.9341 0.8415 0.8976
## [1] "VARIABLES:A7,A64,A82,A25"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73418 -0.17386 -0.04525 0.21231 0.60238
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.21502 1.43512 62.165 2.31e-15 ***
## A7 26.15531 5.42304 4.823 0.000533 ***
## A64 -0.45950 0.16408 -2.800 0.017262 *
## A82 0.03835 0.08940 0.429 0.676195
## A25 -1.24181 0.36714 -3.382 0.006117 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3993 on 11 degrees of freedom
## Multiple R-squared: 0.8637, Adjusted R-squared: 0.8141
## F-statistic: 17.42 on 4 and 11 DF, p-value: 1e-04
##
## A7 A64 A82 A25
## 1.175654 1.361758 1.644471 1.454023
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 8"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 4 0 0
## Medio 5 46 17 0
## Alto 0 0 98 14
## Excelente 0 0 13 120
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7738
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82759 0.9200 0.7656 0.8955
## Specificity 0.98718 0.9244 0.9343 0.9372
## Pos Pred Value 0.85714 0.6765 0.8750 0.9023
## Neg Pred Value 0.98403 0.9853 0.8690 0.9327
## Prevalence 0.08504 0.1466 0.3754 0.3930
## Detection Rate 0.07038 0.1349 0.2874 0.3519
## Detection Prevalence 0.08211 0.1994 0.3284 0.3900
## Balanced Accuracy 0.90738 0.9222 0.8499 0.9164
## [1] "VARIABLES:A56,A64,A36,A7"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.91399 -0.32733 -0.05843 0.44831 0.63409
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 87.3337 2.1204 41.187 2.1e-13 ***
## A56 -0.3718 0.5085 -0.731 0.480
## A64 -0.1982 0.2363 -0.839 0.419
## A36 -0.9599 1.0185 -0.942 0.366
## A7 19.5603 11.7053 1.671 0.123
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5906 on 11 degrees of freedom
## Multiple R-squared: 0.7017, Adjusted R-squared: 0.5933
## F-statistic: 6.47 on 4 and 11 DF, p-value: 0.006263
##
## A56 A64 A36 A7
## 2.478962 1.290664 2.183162 2.503900
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 9"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 1 0 0
## Medio 11 36 14 0
## Alto 0 0 112 18
## Excelente 0 0 14 113
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7478
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.66667 0.9730 0.8000 0.8626
## Specificity 0.99675 0.9178 0.9104 0.9333
## Pos Pred Value 0.95652 0.5902 0.8615 0.8898
## Neg Pred Value 0.96541 0.9964 0.8673 0.9159
## Prevalence 0.09677 0.1085 0.4106 0.3842
## Detection Rate 0.06452 0.1056 0.3284 0.3314
## Detection Prevalence 0.06745 0.1789 0.3812 0.3724
## Balanced Accuracy 0.83171 0.9454 0.8552 0.8980
## [1] "VARIABLES:A7,A64,A6,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.87181 -0.31718 -0.08825 0.37580 0.60332
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.5464 1.0359 82.580 < 2e-16 ***
## A7 36.9181 7.3867 4.998 0.000404 ***
## A64 -0.4264 0.2061 -2.069 0.062876 .
## A6 -0.4686 0.2278 -2.057 0.064152 .
## A9 -4.7672 3.1537 -1.512 0.158808
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5257 on 11 degrees of freedom
## Multiple R-squared: 0.7637, Adjusted R-squared: 0.6778
## F-statistic: 8.89 on 4 and 11 DF, p-value: 0.001861
##
## A7 A64 A6 A9
## 1.258796 1.239613 1.225244 1.148083
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 10"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 0 0 0
## Medio 9 43 10 0
## Alto 0 0 108 18
## Excelente 0 0 13 116
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7843
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.72727 1.0000 0.8244 0.8657
## Specificity 1.00000 0.9362 0.9143 0.9372
## Pos Pred Value 1.00000 0.6935 0.8571 0.8992
## Neg Pred Value 0.97161 1.0000 0.8930 0.9151
## Prevalence 0.09677 0.1261 0.3842 0.3930
## Detection Rate 0.07038 0.1261 0.3167 0.3402
## Detection Prevalence 0.07038 0.1818 0.3695 0.3783
## Balanced Accuracy 0.86364 0.9681 0.8694 0.9014
## [1] "VARIABLES:A7,A64,A6,A3"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0877 -0.3075 0.1048 0.3268 0.7264
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.9164 1.0132 83.812 < 2e-16 ***
## A7 33.5700 8.8755 3.782 0.00303 **
## A64 -0.3936 0.2400 -1.640 0.12918
## A6 -0.4575 0.2635 -1.736 0.11037
## A3 1.9077 3.4569 0.552 0.59209
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5699 on 11 degrees of freedom
## Multiple R-squared: 0.7224, Adjusted R-squared: 0.6214
## F-statistic: 7.155 on 4 and 11 DF, p-value: 0.004323
##
## A7 A64 A6 A3
## 1.546438 1.430241 1.394996 1.708379
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 11"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 2 0 0
## Medio 4 45 11 0
## Alto 0 0 108 22
## Excelente 0 0 15 115
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7632
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82609 0.9574 0.8060 0.8394
## Specificity 0.99371 0.9490 0.8937 0.9265
## Pos Pred Value 0.90476 0.7500 0.8308 0.8846
## Neg Pred Value 0.98750 0.9929 0.8768 0.8957
## Prevalence 0.06745 0.1378 0.3930 0.4018
## Detection Rate 0.05572 0.1320 0.3167 0.3372
## Detection Prevalence 0.06158 0.1760 0.3812 0.3812
## Balanced Accuracy 0.90990 0.9532 0.8498 0.8829
## [1] "VARIABLES:A7,A64,A24,A25"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.71439 -0.19092 -0.00122 0.25462 0.62851
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.5269 1.3749 65.114 1.39e-15 ***
## A7 25.6671 6.3176 4.063 0.00187 **
## A64 -0.4323 0.1532 -2.821 0.01663 *
## A24 -0.1369 0.7928 -0.173 0.86604
## A25 -1.1715 0.9251 -1.266 0.23156
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4021 on 11 degrees of freedom
## Multiple R-squared: 0.8617, Adjusted R-squared: 0.8115
## F-statistic: 17.14 on 4 and 11 DF, p-value: 0.0001078
##
## A7 A64 A24 A25
## 1.573501 1.171395 10.003641 9.104504
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 12"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 5 0 0
## Medio 6 30 13 1
## Alto 0 0 115 14
## Excelente 0 0 15 123
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7591
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76000 0.85714 0.8042 0.8913
## Specificity 0.98418 0.93464 0.9293 0.9261
## Pos Pred Value 0.79167 0.60000 0.8915 0.8913
## Neg Pred Value 0.98107 0.98282 0.8679 0.9261
## Prevalence 0.07331 0.10264 0.4194 0.4047
## Detection Rate 0.05572 0.08798 0.3372 0.3607
## Detection Prevalence 0.07038 0.14663 0.3783 0.4047
## Balanced Accuracy 0.87209 0.89589 0.8667 0.9087
## [1] "VARIABLES:A7,A64,A78,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9934 -0.3769 0.1084 0.4013 0.7388
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.82168 1.52362 56.327 6.82e-15 ***
## A7 30.60344 8.39611 3.645 0.00385 **
## A64 -0.38727 0.24468 -1.583 0.14178
## A78 -0.04579 0.08960 -0.511 0.61942
## A9 -3.48618 3.59429 -0.970 0.35293
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6114 on 11 degrees of freedom
## Multiple R-squared: 0.6804, Adjusted R-squared: 0.5642
## F-statistic: 5.855 on 4 and 11 DF, p-value: 0.008937
##
## A7 A64 A78 A9
## 1.202294 1.291897 1.119377 1.102479
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 13"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 3 0 0
## Medio 5 47 9 0
## Alto 0 0 112 21
## Excelente 0 0 15 109
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7696
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80000 0.9400 0.8235 0.8385
## Specificity 0.99051 0.9519 0.8976 0.9289
## Pos Pred Value 0.86957 0.7705 0.8421 0.8790
## Neg Pred Value 0.98428 0.9893 0.8846 0.9032
## Prevalence 0.07331 0.1466 0.3988 0.3812
## Detection Rate 0.05865 0.1378 0.3284 0.3196
## Detection Prevalence 0.06745 0.1789 0.3900 0.3636
## Balanced Accuracy 0.89525 0.9459 0.8605 0.8837
## [1] "VARIABLES:A7,A64,A82,A36"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64235 -0.38618 -0.04374 0.26729 0.88930
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.3556 1.4158 60.993 2.85e-15 ***
## A7 23.0191 8.7224 2.639 0.0230 *
## A64 -0.3600 0.2332 -1.544 0.1510
## A82 0.1850 0.1028 1.800 0.0994 .
## A36 -1.1228 0.8704 -1.290 0.2235
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5316 on 11 degrees of freedom
## Multiple R-squared: 0.7584, Adjusted R-squared: 0.6705
## F-statistic: 8.632 on 4 and 11 DF, p-value: 0.002092
##
## A7 A64 A82 A36
## 1.716346 1.552935 1.227004 1.968240
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 14"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 3 0 0
## Medio 6 43 8 10
## Alto 0 0 105 16
## Excelente 0 0 13 117
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7576
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76923 0.9348 0.8333 0.8182
## Specificity 0.99048 0.9186 0.9256 0.9343
## Pos Pred Value 0.86957 0.6418 0.8678 0.9000
## Neg Pred Value 0.98113 0.9891 0.9045 0.8768
## Prevalence 0.07625 0.1349 0.3695 0.4194
## Detection Rate 0.05865 0.1261 0.3079 0.3431
## Detection Prevalence 0.06745 0.1965 0.3548 0.3812
## Balanced Accuracy 0.87985 0.9267 0.8795 0.8763
## [1] "VARIABLES:A7,A64,A37,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68202 -0.29794 -0.00586 0.40977 0.80494
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.4351 1.0529 81.144 < 2e-16 ***
## A7 30.0093 7.1476 4.198 0.00149 **
## A64 -0.2288 0.2174 -1.052 0.31532
## A37 -10.3675 5.4328 -1.908 0.08278 .
## A9 0.5632 3.7960 0.148 0.88474
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5362 on 11 degrees of freedom
## Multiple R-squared: 0.7542, Adjusted R-squared: 0.6648
## F-statistic: 8.438 on 4 and 11 DF, p-value: 0.00229
##
## A7 A64 A37 A9
## 1.132883 1.326347 1.493141 1.598844
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 15"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 2 0 1
## Medio 4 46 6 0
## Alto 0 0 110 34
## Excelente 0 0 7 107
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7667
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.85714 0.9583 0.8943 0.7535
## Specificity 0.99042 0.9659 0.8440 0.9648
## Pos Pred Value 0.88889 0.8214 0.7639 0.9386
## Neg Pred Value 0.98726 0.9930 0.9340 0.8458
## Prevalence 0.08211 0.1408 0.3607 0.4164
## Detection Rate 0.07038 0.1349 0.3226 0.3138
## Detection Prevalence 0.07918 0.1642 0.4223 0.3343
## Balanced Accuracy 0.92378 0.9621 0.8692 0.8592
## [1] "VARIABLES:A7,A64,A41,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.02228 -0.42069 0.04795 0.38317 0.77293
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.97057 2.02002 41.569 1.9e-13 ***
## A7 31.90474 8.42971 3.785 0.00302 **
## A64 -0.21200 0.31442 -0.674 0.51407
## A41 1.02625 2.57477 0.399 0.69783
## A38 0.05376 0.09851 0.546 0.59613
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6349 on 11 degrees of freedom
## Multiple R-squared: 0.6553, Adjusted R-squared: 0.53
## F-statistic: 5.229 on 4 and 11 DF, p-value: 0.01315
##
## A7 A64 A41 A38
## 1.123756 1.978154 2.430631 1.530222
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 16"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 7 45 17 0
## Alto 0 0 105 18
## Excelente 0 0 13 110
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7611
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78125 0.9783 0.7778 0.8594
## Specificity 0.99676 0.9186 0.9126 0.9390
## Pos Pred Value 0.96154 0.6522 0.8537 0.8943
## Neg Pred Value 0.97778 0.9963 0.8624 0.9174
## Prevalence 0.09384 0.1349 0.3959 0.3754
## Detection Rate 0.07331 0.1320 0.3079 0.3226
## Detection Prevalence 0.07625 0.2023 0.3607 0.3607
## Balanced Accuracy 0.88901 0.9485 0.8452 0.8992
## [1] "VARIABLES:A7,A64,A35,A24,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6003 -0.1908 0.0307 0.1656 0.5411
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.7965 1.3950 63.655 2.23e-14 ***
## A7 22.6521 5.4560 4.152 0.00197 **
## A64 -0.3756 0.1461 -2.571 0.02783 *
## A35 -13.0736 7.0124 -1.864 0.09186 .
## A24 -0.8071 0.2994 -2.696 0.02247 *
## A77 0.1953 0.8737 0.224 0.82758
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3786 on 10 degrees of freedom
## Multiple R-squared: 0.8886, Adjusted R-squared: 0.8329
## F-statistic: 15.95 on 5 and 10 DF, p-value: 0.000174
##
## A7 A64 A35 A24 A77
## 1.323861 1.201059 1.508869 1.609029 1.139796
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 17"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 3 0 0
## Medio 6 40 12 2
## Alto 0 0 124 24
## Excelente 0 0 7 105
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.762
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9302 0.8671 0.8015
## Specificity 0.99054 0.9329 0.8788 0.9667
## Pos Pred Value 0.85714 0.6667 0.8378 0.9375
## Neg Pred Value 0.98125 0.9893 0.9016 0.8865
## Prevalence 0.07038 0.1261 0.4194 0.3842
## Detection Rate 0.05279 0.1173 0.3636 0.3079
## Detection Prevalence 0.06158 0.1760 0.4340 0.3284
## Balanced Accuracy 0.87027 0.9316 0.8730 0.8841
## [1] "VARIABLES:A7,A64,A36,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85906 -0.39283 -0.09191 0.50578 0.61586
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.11470 1.79495 47.976 3.96e-14 ***
## A7 24.75370 9.98842 2.478 0.0307 *
## A64 -0.18995 0.24167 -0.786 0.4485
## A36 -1.16179 0.99866 -1.163 0.2693
## A38 0.01724 0.07703 0.224 0.8270
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6034 on 11 degrees of freedom
## Multiple R-squared: 0.6887, Adjusted R-squared: 0.5755
## F-statistic: 6.083 on 4 and 11 DF, p-value: 0.007813
##
## A7 A64 A36 A38
## 1.746648 1.293712 2.010721 1.035612
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 18"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 16 0 0 0
## Medio 5 28 4 0
## Alto 0 16 126 27
## Excelente 0 0 9 110
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7209
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76190 0.63636 0.9065 0.8029
## Specificity 1.00000 0.96970 0.7871 0.9559
## Pos Pred Value 1.00000 0.75676 0.7456 0.9244
## Neg Pred Value 0.98462 0.94737 0.9244 0.8784
## Prevalence 0.06158 0.12903 0.4076 0.4018
## Detection Rate 0.04692 0.08211 0.3695 0.3226
## Detection Prevalence 0.04692 0.10850 0.4956 0.3490
## Balanced Accuracy 0.88095 0.80303 0.8468 0.8794
## [1] "VARIABLES:A7,A7,A6,A76"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9132 -0.2851 0.1074 0.3108 0.7741
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.6914 0.8845 94.619 < 2e-16 ***
## A7 40.5017 7.3429 5.516 0.000133 ***
## A6 -0.4055 0.2296 -1.766 0.102780
## A76 0.3156 0.1745 1.809 0.095611 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5406 on 12 degrees of freedom
## Multiple R-squared: 0.7274, Adjusted R-squared: 0.6593
## F-statistic: 10.67 on 3 and 12 DF, p-value: 0.001053
##
## A7 A6 A76
## 1.176176 1.177329 1.020461
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 19"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 1 0 2
## Medio 7 44 13 1
## Alto 0 0 104 20
## Excelente 0 0 13 115
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7537
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9778 0.8000 0.8333
## Specificity 0.99042 0.9291 0.9052 0.9360
## Pos Pred Value 0.87500 0.6769 0.8387 0.8984
## Neg Pred Value 0.97792 0.9964 0.8802 0.8920
## Prevalence 0.08211 0.1320 0.3812 0.4047
## Detection Rate 0.06158 0.1290 0.3050 0.3372
## Detection Prevalence 0.07038 0.1906 0.3636 0.3754
## Balanced Accuracy 0.87021 0.9534 0.8526 0.8846
## [1] "VARIABLES:A7,A64,A64,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 20"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 2 0 0
## Medio 9 43 7 0
## Alto 0 0 99 19
## Excelente 0 0 15 118
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7782
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76316 0.9556 0.8182 0.8613
## Specificity 0.99340 0.9459 0.9136 0.9265
## Pos Pred Value 0.93548 0.7288 0.8390 0.8872
## Neg Pred Value 0.97097 0.9929 0.9013 0.9087
## Prevalence 0.11144 0.1320 0.3548 0.4018
## Detection Rate 0.08504 0.1261 0.2903 0.3460
## Detection Prevalence 0.09091 0.1730 0.3460 0.3900
## Balanced Accuracy 0.87828 0.9508 0.8659 0.8939
## [1] "VARIABLES:A7,A64,A60,A82"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.62316 -0.44615 0.08399 0.28545 0.70208
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.6077 0.9761 86.679 < 2e-16 ***
## A7 27.4360 7.2059 3.807 0.00291 **
## A64 -0.5316 0.2219 -2.395 0.03553 *
## A60 1.2913 0.9438 1.368 0.19857
## A82 0.2294 0.1056 2.172 0.05258 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5273 on 11 degrees of freedom
## Multiple R-squared: 0.7623, Adjusted R-squared: 0.6759
## F-statistic: 8.819 on 4 and 11 DF, p-value: 0.001921
##
## A7 A64 A60 A82
## 1.190629 1.429028 1.112896 1.316347
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 21"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 4 0 2
## Medio 9 31 12 1
## Alto 0 0 113 18
## Excelente 0 0 16 113
##
## Overall Statistics
##
## Accuracy : 0.8182
## 95% CI : (0.7731, 0.8577)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7283
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.70968 0.88571 0.8014 0.8433
## Specificity 0.98065 0.92810 0.9100 0.9227
## Pos Pred Value 0.78571 0.58491 0.8626 0.8760
## Neg Pred Value 0.97125 0.98611 0.8667 0.9009
## Prevalence 0.09091 0.10264 0.4135 0.3930
## Detection Rate 0.06452 0.09091 0.3314 0.3314
## Detection Prevalence 0.08211 0.15543 0.3842 0.3783
## Balanced Accuracy 0.84516 0.90691 0.8557 0.8830
## [1] "VARIABLES:A7,A64,A64,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13108 -0.43106 0.04603 0.38812 0.78935
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4781 1.4106 59.886 3.11e-16 ***
## A7 31.7573 8.1277 3.907 0.00208 **
## A64 -0.2980 0.2280 -1.307 0.21559
## A77 0.5294 1.3378 0.396 0.69926
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6123 on 12 degrees of freedom
## Multiple R-squared: 0.6503, Adjusted R-squared: 0.5628
## F-statistic: 7.437 on 3 and 12 DF, p-value: 0.004489
##
## A7 A64 A77
## 1.123108 1.117863 1.021665
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 22"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 4 0 0
## Medio 5 41 15 3
## Alto 0 0 127 15
## Excelente 0 0 13 97
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4545
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7598
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80769 0.9111 0.8194 0.8435
## Specificity 0.98730 0.9223 0.9194 0.9425
## Pos Pred Value 0.84000 0.6406 0.8944 0.8818
## Neg Pred Value 0.98418 0.9856 0.8593 0.9221
## Prevalence 0.07625 0.1320 0.4545 0.3372
## Detection Rate 0.06158 0.1202 0.3724 0.2845
## Detection Prevalence 0.07331 0.1877 0.4164 0.3226
## Balanced Accuracy 0.89750 0.9167 0.8694 0.8930
## [1] "VARIABLES:A7,A64,A25,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64213 -0.16992 -0.04091 0.27628 0.50961
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.9156 1.2676 70.146 6.14e-16 ***
## A7 26.6358 5.0065 5.320 0.000245 ***
## A64 -0.4558 0.1411 -3.230 0.008008 **
## A25 -1.3973 0.2966 -4.711 0.000639 ***
## A77 1.1995 0.8169 1.468 0.169991
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3682 on 11 degrees of freedom
## Multiple R-squared: 0.8841, Adjusted R-squared: 0.8419
## F-statistic: 20.98 on 4 and 11 DF, p-value: 4.175e-05
##
## A7 A64 A25 A77
## 1.178689 1.184632 1.116400 1.053620
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 23"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 4 0 0
## Medio 3 37 9 2
## Alto 0 0 118 21
## Excelente 0 0 14 112
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7652
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.87500 0.9024 0.8369 0.8296
## Specificity 0.98738 0.9533 0.8950 0.9320
## Pos Pred Value 0.84000 0.7255 0.8489 0.8889
## Neg Pred Value 0.99051 0.9862 0.8861 0.8930
## Prevalence 0.07038 0.1202 0.4135 0.3959
## Detection Rate 0.06158 0.1085 0.3460 0.3284
## Detection Prevalence 0.07331 0.1496 0.4076 0.3695
## Balanced Accuracy 0.93119 0.9279 0.8659 0.8808
## [1] "VARIABLES:A7,A64,A25,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74558 -0.18833 0.00015 0.24524 0.61690
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.4597 1.3251 67.513 9.34e-16 ***
## A7 26.2744 5.5073 4.771 0.00058 ***
## A64 -0.4360 0.1569 -2.778 0.01797 *
## A25 -1.3118 0.3389 -3.870 0.00261 **
## A9 -0.2136 2.5119 -0.085 0.93376
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4025 on 11 degrees of freedom
## Multiple R-squared: 0.8615, Adjusted R-squared: 0.8111
## F-statistic: 17.1 on 4 and 11 DF, p-value: 0.000109
##
## A7 A64 A25 A9
## 1.193305 1.226119 1.219680 1.242083
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 24"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 2 0 0
## Medio 5 44 12 2
## Alto 0 0 99 22
## Excelente 0 0 19 109
##
## Overall Statistics
##
## Accuracy : 0.8182
## 95% CI : (0.7731, 0.8577)
## No Information Rate : 0.39
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7347
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.84375 0.9565 0.7615 0.8195
## Specificity 0.99353 0.9356 0.8957 0.9087
## Pos Pred Value 0.93103 0.6984 0.8182 0.8516
## Neg Pred Value 0.98397 0.9928 0.8591 0.8873
## Prevalence 0.09384 0.1349 0.3812 0.3900
## Detection Rate 0.07918 0.1290 0.2903 0.3196
## Detection Prevalence 0.08504 0.1848 0.3548 0.3754
## Balanced Accuracy 0.91864 0.9461 0.8286 0.8641
## [1] "VARIABLES:A7,A64,A41,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13290 -0.42791 0.05098 0.38411 0.78624
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.5089 1.5809 53.457 1.21e-14 ***
## A7 31.7777 8.4965 3.740 0.00327 **
## A64 -0.3086 0.3094 -0.998 0.33989
## A41 -0.1232 2.2909 -0.054 0.95809
## A77 0.5613 1.5180 0.370 0.71858
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6395 on 11 degrees of freedom
## Multiple R-squared: 0.6504, Adjusted R-squared: 0.5232
## F-statistic: 5.115 on 4 and 11 DF, p-value: 0.01414
##
## A7 A64 A41 A77
## 1.125359 1.887812 1.896855 1.206150
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 25"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 4 0 0
## Medio 4 47 16 2
## Alto 0 0 105 17
## Excelente 0 0 11 112
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.3871
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7693
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.85185 0.9216 0.7955 0.8550
## Specificity 0.98726 0.9241 0.9187 0.9476
## Pos Pred Value 0.85185 0.6812 0.8607 0.9106
## Neg Pred Value 0.98726 0.9853 0.8767 0.9128
## Prevalence 0.07918 0.1496 0.3871 0.3842
## Detection Rate 0.06745 0.1378 0.3079 0.3284
## Detection Prevalence 0.07918 0.2023 0.3578 0.3607
## Balanced Accuracy 0.91956 0.9229 0.8571 0.9013
## [1] "VARIABLES:A7,A64,A36,A57,A40"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.66177 -0.37001 0.05586 0.24116 0.64671
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 87.83998 1.47698 59.473 4.39e-14 ***
## A7 19.14136 8.45348 2.264 0.0470 *
## A64 -0.21675 0.20652 -1.050 0.3186
## A36 0.54293 1.09673 0.495 0.6313
## A57 -0.07789 0.19382 -0.402 0.6962
## A40 -2.25061 0.94746 -2.375 0.0389 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5004 on 10 degrees of freedom
## Multiple R-squared: 0.8054, Adjusted R-squared: 0.7081
## F-statistic: 8.278 on 5 and 10 DF, p-value: 0.002511
##
## A7 A64 A36 A57 A40
## 1.819655 1.374079 3.527116 1.311371 3.365786
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 26"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 9 37 10 0
## Alto 0 0 111 25
## Excelente 0 0 18 109
##
## Overall Statistics
##
## Accuracy : 0.8123
## 95% CI : (0.7668, 0.8524)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7185
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.68966 0.9487 0.7986 0.8134
## Specificity 0.99359 0.9371 0.8762 0.9130
## Pos Pred Value 0.90909 0.6607 0.8162 0.8583
## Neg Pred Value 0.97179 0.9930 0.8634 0.8832
## Prevalence 0.08504 0.1144 0.4076 0.3930
## Detection Rate 0.05865 0.1085 0.3255 0.3196
## Detection Prevalence 0.06452 0.1642 0.3988 0.3724
## Balanced Accuracy 0.84162 0.9429 0.8374 0.8632
## [1] "VARIABLES:A7,A64,A82,A37"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.61875 -0.30466 0.09759 0.18810 0.78626
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.57324 0.86803 98.583 < 2e-16 ***
## A7 28.57477 6.26661 4.560 0.000817 ***
## A64 -0.39883 0.19468 -2.049 0.065128 .
## A82 0.16868 0.09103 1.853 0.090874 .
## A37 -9.12932 3.96509 -2.302 0.041853 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4685 on 11 degrees of freedom
## Multiple R-squared: 0.8123, Adjusted R-squared: 0.7441
## F-statistic: 11.9 on 4 and 11 DF, p-value: 0.0005518
##
## A7 A64 A82 A37
## 1.140369 1.392528 1.238617 1.041553
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 27"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 0
## Medio 8 23 3 0
## Alto 0 15 129 22
## Excelente 0 0 9 108
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7338
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 0.57500 0.9149 0.8308
## Specificity 0.99357 0.96346 0.8150 0.9573
## Pos Pred Value 0.91667 0.67647 0.7771 0.9231
## Neg Pred Value 0.97476 0.94463 0.9314 0.9018
## Prevalence 0.08798 0.11730 0.4135 0.3812
## Detection Rate 0.06452 0.06745 0.3783 0.3167
## Detection Prevalence 0.07038 0.09971 0.4868 0.3431
## Balanced Accuracy 0.86345 0.76923 0.8649 0.8941
## [1] "VARIABLES:A7,A7,A60,A62"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.15756 -0.44862 0.02686 0.34822 0.94269
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.0624 1.0673 78.764 < 2e-16 ***
## A7 36.5578 8.3718 4.367 0.000917 ***
## A60 0.2333 1.1420 0.204 0.841562
## A62 -1.6268 1.7515 -0.929 0.371285
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.627 on 12 degrees of freedom
## Multiple R-squared: 0.6333, Adjusted R-squared: 0.5416
## F-statistic: 6.909 on 3 and 12 DF, p-value: 0.0059
##
## A7 A60 A62
## 1.136516 1.152254 1.208387
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 28"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 4 0 0
## Medio 5 45 13 0
## Alto 0 0 108 20
## Excelente 0 0 17 104
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7474
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.83333 0.9184 0.7826 0.8387
## Specificity 0.98714 0.9384 0.9015 0.9217
## Pos Pred Value 0.86207 0.7143 0.8438 0.8595
## Neg Pred Value 0.98397 0.9856 0.8592 0.9091
## Prevalence 0.08798 0.1437 0.4047 0.3636
## Detection Rate 0.07331 0.1320 0.3167 0.3050
## Detection Prevalence 0.08504 0.1848 0.3754 0.3548
## Balanced Accuracy 0.91024 0.9284 0.8420 0.8802
## [1] "VARIABLES:A7,A64,A36,A12,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84666 -0.40317 -0.03485 0.49826 0.54317
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.7456 1.8566 46.724 4.86e-13 ***
## A7 22.7974 13.3155 1.712 0.118
## A64 -0.2537 0.2620 -0.968 0.356
## A36 -1.2570 1.2453 -1.009 0.337
## A12 1.1167 3.3495 0.333 0.746
## A9 -1.7231 4.5845 -0.376 0.715
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.616 on 10 degrees of freedom
## Multiple R-squared: 0.7051, Adjusted R-squared: 0.5576
## F-statistic: 4.781 on 5 and 10 DF, p-value: 0.01716
##
## A7 A64 A36 A12 A9
## 2.978823 1.459084 3.000336 2.223219 1.766838
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 29"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 6 48 17 1
## Alto 0 0 101 17
## Excelente 0 0 14 115
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.39
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7551
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76923 0.9600 0.7652 0.8647
## Specificity 0.99365 0.9175 0.9187 0.9327
## Pos Pred Value 0.90909 0.6667 0.8559 0.8915
## Neg Pred Value 0.98119 0.9926 0.8610 0.9151
## Prevalence 0.07625 0.1466 0.3871 0.3900
## Detection Rate 0.05865 0.1408 0.2962 0.3372
## Detection Prevalence 0.06452 0.2111 0.3460 0.3783
## Balanced Accuracy 0.88144 0.9388 0.8419 0.8987
## [1] "VARIABLES:A7,A64,A53,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.58861 -0.21181 -0.08127 0.28937 0.71139
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.28099 0.89943 95.929 < 2e-16 ***
## A7 27.09293 5.92544 4.572 0.00080 ***
## A64 -0.06343 0.18950 -0.335 0.74414
## A53 -5.55256 1.66027 -3.344 0.00654 **
## A9 -3.82394 2.56289 -1.492 0.16380
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4356 on 11 degrees of freedom
## Multiple R-squared: 0.8378, Adjusted R-squared: 0.7788
## F-statistic: 14.2 on 4 and 11 DF, p-value: 0.0002537
##
## A7 A64 A53 A9
## 1.179688 1.526592 1.499922 1.104273
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 30"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 3 0 0
## Medio 6 48 14 2
## Alto 0 0 112 13
## Excelente 0 0 12 108
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7867
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.79310 0.9412 0.8116 0.8780
## Specificity 0.99038 0.9241 0.9360 0.9450
## Pos Pred Value 0.88462 0.6857 0.8960 0.9000
## Neg Pred Value 0.98095 0.9889 0.8796 0.9321
## Prevalence 0.08504 0.1496 0.4047 0.3607
## Detection Rate 0.06745 0.1408 0.3284 0.3167
## Detection Prevalence 0.07625 0.2053 0.3666 0.3519
## Balanced Accuracy 0.89174 0.9327 0.8738 0.9115
## [1] "VARIABLES:A7,A64,A36,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.83973 -0.31650 -0.08494 0.52077 0.64406
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.8742 1.5744 54.545 9.7e-15 ***
## A7 22.2960 9.5705 2.330 0.0399 *
## A64 -0.1580 0.2302 -0.687 0.5066
## A36 -1.7110 1.0480 -1.633 0.1308
## A77 1.5463 1.3999 1.105 0.2929
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5738 on 11 degrees of freedom
## Multiple R-squared: 0.7185, Adjusted R-squared: 0.6161
## F-statistic: 7.018 on 4 and 11 DF, p-value: 0.004646
##
## A7 A64 A36 A77
## 1.773333 1.297960 2.448787 1.273879
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 31"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 2 0 0
## Medio 5 48 15 6
## Alto 0 0 101 20
## Excelente 0 0 15 112
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7273
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.77273 0.9600 0.7710 0.8116
## Specificity 0.99373 0.9107 0.9048 0.9261
## Pos Pred Value 0.89474 0.6486 0.8347 0.8819
## Neg Pred Value 0.98447 0.9925 0.8636 0.8785
## Prevalence 0.06452 0.1466 0.3842 0.4047
## Detection Rate 0.04985 0.1408 0.2962 0.3284
## Detection Prevalence 0.05572 0.2170 0.3548 0.3724
## Balanced Accuracy 0.88323 0.9353 0.8379 0.8689
## [1] "VARIABLES:A7,A64,A37,A44"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.65331 -0.32052 -0.04957 0.29058 0.77172
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.2673 0.9278 91.898 < 2e-16 ***
## A7 28.7399 6.6261 4.337 0.00118 **
## A64 -0.3473 0.1996 -1.740 0.10979
## A37 -7.3569 4.5422 -1.620 0.13359
## A44 0.5198 0.3706 1.403 0.18828
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4943 on 11 degrees of freedom
## Multiple R-squared: 0.7911, Adjusted R-squared: 0.7151
## F-statistic: 10.41 on 4 and 11 DF, p-value: 0.0009733
##
## A7 A64 A37 A44
## 1.145450 1.315364 1.228001 1.329229
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 32"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 3 0 0
## Medio 6 36 11 1
## Alto 0 0 128 25
## Excelente 0 0 3 103
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7855
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80645 0.9231 0.9014 0.7984
## Specificity 0.99032 0.9404 0.8744 0.9858
## Pos Pred Value 0.89286 0.6667 0.8366 0.9717
## Neg Pred Value 0.98083 0.9895 0.9255 0.8894
## Prevalence 0.09091 0.1144 0.4164 0.3783
## Detection Rate 0.07331 0.1056 0.3754 0.3021
## Detection Prevalence 0.08211 0.1584 0.4487 0.3109
## Balanced Accuracy 0.89839 0.9317 0.8879 0.8921
## [1] "VARIABLES:A7,A64,A36,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85906 -0.39283 -0.09191 0.50578 0.61586
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.11470 1.79495 47.976 3.96e-14 ***
## A7 24.75370 9.98842 2.478 0.0307 *
## A64 -0.18995 0.24167 -0.786 0.4485
## A36 -1.16179 0.99866 -1.163 0.2693
## A38 0.01724 0.07703 0.224 0.8270
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6034 on 11 degrees of freedom
## Multiple R-squared: 0.6887, Adjusted R-squared: 0.5755
## F-statistic: 6.083 on 4 and 11 DF, p-value: 0.007813
##
## A7 A64 A36 A38
## 1.746648 1.293712 2.010721 1.035612
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 33"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 2 0 0
## Medio 10 30 6 1
## Alto 0 18 116 20
## Excelente 0 0 13 107
##
## Overall Statistics
##
## Accuracy : 0.7947
## 95% CI : (0.7479, 0.8363)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6909
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.64286 0.60000 0.8593 0.8359
## Specificity 0.99361 0.94158 0.8155 0.9390
## Pos Pred Value 0.90000 0.63830 0.7532 0.8917
## Neg Pred Value 0.96885 0.93197 0.8984 0.9050
## Prevalence 0.08211 0.14663 0.3959 0.3754
## Detection Rate 0.05279 0.08798 0.3402 0.3138
## Detection Prevalence 0.05865 0.13783 0.4516 0.3519
## Balanced Accuracy 0.81823 0.77079 0.8374 0.8875
## [1] "VARIABLES:A7,A7,A33,A10"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.26831 -0.20924 -0.03291 0.36287 0.85644
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.553 1.207 70.047 < 2e-16 ***
## A7 30.929 9.182 3.368 0.00559 **
## A33 -1.635 10.231 -0.160 0.87567
## A10 1.620 2.361 0.686 0.50565
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6339 on 12 degrees of freedom
## Multiple R-squared: 0.6252, Adjusted R-squared: 0.5315
## F-statistic: 6.673 on 3 and 12 DF, p-value: 0.00669
##
## A7 A33 A10
## 1.337620 1.457159 1.859426
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 34"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 1 0 0
## Medio 7 40 12 5
## Alto 0 0 111 32
## Excelente 0 0 6 106
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7266
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9756 0.8605 0.7413
## Specificity 0.99681 0.9200 0.8491 0.9697
## Pos Pred Value 0.95455 0.6250 0.7762 0.9464
## Neg Pred Value 0.97806 0.9964 0.9091 0.8384
## Prevalence 0.08211 0.1202 0.3783 0.4194
## Detection Rate 0.06158 0.1173 0.3255 0.3109
## Detection Prevalence 0.06452 0.1877 0.4194 0.3284
## Balanced Accuracy 0.87340 0.9478 0.8548 0.8555
## [1] "VARIABLES:A7,A64,A37,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68959 -0.31891 0.02216 0.37252 0.80056
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.59856 1.18539 72.211 4.46e-16 ***
## A7 29.98489 7.14984 4.194 0.0015 **
## A64 -0.23883 0.20084 -1.189 0.2594
## A37 -10.14550 4.70110 -2.158 0.0539 .
## A38 -0.01206 0.07049 -0.171 0.8673
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.536 on 11 degrees of freedom
## Multiple R-squared: 0.7544, Adjusted R-squared: 0.665
## F-statistic: 8.446 on 4 and 11 DF, p-value: 0.002282
##
## A7 A64 A37 A38
## 1.134334 1.132517 1.118777 1.099200
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 35"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 3 0 0
## Medio 6 40 12 0
## Alto 0 0 106 16
## Excelente 0 0 12 122
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7875
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80000 0.9302 0.8154 0.8841
## Specificity 0.99035 0.9396 0.9242 0.9409
## Pos Pred Value 0.88889 0.6897 0.8689 0.9104
## Neg Pred Value 0.98089 0.9894 0.8904 0.9227
## Prevalence 0.08798 0.1261 0.3812 0.4047
## Detection Rate 0.07038 0.1173 0.3109 0.3578
## Detection Prevalence 0.07918 0.1701 0.3578 0.3930
## Balanced Accuracy 0.89518 0.9349 0.8698 0.9125
## [1] "VARIABLES:A7,A64,A82,A25"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73418 -0.17386 -0.04525 0.21231 0.60238
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.21502 1.43512 62.165 2.31e-15 ***
## A7 26.15531 5.42304 4.823 0.000533 ***
## A64 -0.45950 0.16408 -2.800 0.017262 *
## A82 0.03835 0.08940 0.429 0.676195
## A25 -1.24181 0.36714 -3.382 0.006117 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3993 on 11 degrees of freedom
## Multiple R-squared: 0.8637, Adjusted R-squared: 0.8141
## F-statistic: 17.42 on 4 and 11 DF, p-value: 1e-04
##
## A7 A64 A82 A25
## 1.175654 1.361758 1.644471 1.454023
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 36"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 16 2 0 0
## Medio 6 47 13 3
## Alto 0 0 106 18
## Excelente 0 0 14 116
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7558
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.72727 0.9592 0.7970 0.8467
## Specificity 0.99373 0.9247 0.9135 0.9314
## Pos Pred Value 0.88889 0.6812 0.8548 0.8923
## Neg Pred Value 0.98142 0.9926 0.8756 0.9005
## Prevalence 0.06452 0.1437 0.3900 0.4018
## Detection Rate 0.04692 0.1378 0.3109 0.3402
## Detection Prevalence 0.05279 0.2023 0.3636 0.3812
## Balanced Accuracy 0.86050 0.9419 0.8552 0.8890
## [1] "VARIABLES:A7,A64,A25,A36"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.72979 -0.19265 0.00728 0.22021 0.62644
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.51483 1.37699 65.008 1.41e-15 ***
## A7 25.70704 6.58507 3.904 0.00246 **
## A64 -0.42211 0.17264 -2.445 0.03253 *
## A25 -1.30167 0.34964 -3.723 0.00336 **
## A36 -0.09977 0.72089 -0.138 0.89243
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4023 on 11 degrees of freedom
## Multiple R-squared: 0.8616, Adjusted R-squared: 0.8113
## F-statistic: 17.12 on 4 and 11 DF, p-value: 0.0001083
##
## A7 A64 A25 A36
## 1.707905 1.485260 1.299264 2.357135
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 37"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 1 0 0
## Medio 5 44 16 0
## Alto 0 0 112 12
## Excelente 0 0 18 111
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4282
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7749
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.81481 0.9778 0.7671 0.9024
## Specificity 0.99682 0.9291 0.9385 0.9174
## Pos Pred Value 0.95652 0.6769 0.9032 0.8605
## Neg Pred Value 0.98428 0.9964 0.8433 0.9434
## Prevalence 0.07918 0.1320 0.4282 0.3607
## Detection Rate 0.06452 0.1290 0.3284 0.3255
## Detection Prevalence 0.06745 0.1906 0.3636 0.3783
## Balanced Accuracy 0.90582 0.9534 0.8528 0.9099
## [1] "VARIABLES:A7,A64,A41,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97124 -0.41033 0.08358 0.42657 0.72967
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.1067 1.4352 59.300 3.88e-15 ***
## A7 31.7803 8.1439 3.902 0.00247 **
## A64 -0.3066 0.2861 -1.072 0.30686
## A41 0.6288 2.0742 0.303 0.76744
## A9 -3.7005 3.6983 -1.001 0.33852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.616 on 11 degrees of freedom
## Multiple R-squared: 0.6755, Adjusted R-squared: 0.5576
## F-statistic: 5.726 on 4 and 11 DF, p-value: 0.009658
##
## A7 A64 A41 A9
## 1.114140 1.739638 1.675546 1.149645
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 38"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 0 0 2
## Medio 8 40 16 1
## Alto 0 0 125 15
## Excelente 0 0 14 102
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4545
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7537
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.69231 1.0000 0.8065 0.8500
## Specificity 0.99365 0.9169 0.9194 0.9367
## Pos Pred Value 0.90000 0.6154 0.8929 0.8793
## Neg Pred Value 0.97508 1.0000 0.8507 0.9200
## Prevalence 0.07625 0.1173 0.4545 0.3519
## Detection Rate 0.05279 0.1173 0.3666 0.2991
## Detection Prevalence 0.05865 0.1906 0.4106 0.3402
## Balanced Accuracy 0.84298 0.9585 0.8629 0.8933
## [1] "VARIABLES:A7,A64,A64,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13108 -0.43106 0.04603 0.38812 0.78935
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4781 1.4106 59.886 3.11e-16 ***
## A7 31.7573 8.1277 3.907 0.00208 **
## A64 -0.2980 0.2280 -1.307 0.21559
## A77 0.5294 1.3378 0.396 0.69926
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6123 on 12 degrees of freedom
## Multiple R-squared: 0.6503, Adjusted R-squared: 0.5628
## F-statistic: 7.437 on 3 and 12 DF, p-value: 0.004489
##
## A7 A64 A77
## 1.123108 1.117863 1.021665
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 39"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 0 0 0
## Medio 8 38 16 0
## Alto 0 0 109 18
## Excelente 0 0 18 114
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.737
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 1.0000 0.7622 0.8636
## Specificity 1.00000 0.9208 0.9091 0.9139
## Pos Pred Value 1.00000 0.6129 0.8583 0.8636
## Neg Pred Value 0.97508 1.0000 0.8411 0.9139
## Prevalence 0.08211 0.1114 0.4194 0.3871
## Detection Rate 0.05865 0.1114 0.3196 0.3343
## Detection Prevalence 0.05865 0.1818 0.3724 0.3871
## Balanced Accuracy 0.85714 0.9604 0.8357 0.8888
## [1] "VARIABLES:A7,A64,A60,A29"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.87507 -0.36513 -0.02939 0.40707 0.75915
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4785 1.1438 73.858 3.49e-16 ***
## A7 29.5264 8.2970 3.559 0.00448 **
## A64 -0.2798 0.2320 -1.206 0.25305
## A60 0.6979 1.0598 0.658 0.52378
## A29 4.3594 5.4626 0.798 0.44173
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6128 on 11 degrees of freedom
## Multiple R-squared: 0.6789, Adjusted R-squared: 0.5622
## F-statistic: 5.815 on 4 and 11 DF, p-value: 0.009152
##
## A7 A64 A60 A29
## 1.168636 1.156192 1.038936 1.072604
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 40"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 1 0 0
## Medio 7 39 13 2
## Alto 0 0 117 15
## Excelente 0 0 18 110
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.434
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7537
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73077 0.9750 0.7905 0.8661
## Specificity 0.99683 0.9269 0.9223 0.9159
## Pos Pred Value 0.95000 0.6393 0.8864 0.8594
## Neg Pred Value 0.97819 0.9964 0.8517 0.9202
## Prevalence 0.07625 0.1173 0.4340 0.3724
## Detection Rate 0.05572 0.1144 0.3431 0.3226
## Detection Prevalence 0.05865 0.1789 0.3871 0.3754
## Balanced Accuracy 0.86380 0.9510 0.8564 0.8910
## [1] "VARIABLES:A7,A64,A7,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 41"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 5 40 12 0
## Alto 0 0 110 14
## Excelente 0 0 14 124
##
## Overall Statistics
##
## Accuracy : 0.8622
## 95% CI : (0.821, 0.8969)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.793
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80000 0.9524 0.8088 0.8986
## Specificity 0.99367 0.9431 0.9317 0.9310
## Pos Pred Value 0.90909 0.7018 0.8871 0.8986
## Neg Pred Value 0.98433 0.9930 0.8802 0.9310
## Prevalence 0.07331 0.1232 0.3988 0.4047
## Detection Rate 0.05865 0.1173 0.3226 0.3636
## Detection Prevalence 0.06452 0.1672 0.3636 0.4047
## Balanced Accuracy 0.89684 0.9478 0.8703 0.9148
## [1] "VARIABLES:A7,A64,A7,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13108 -0.43106 0.04603 0.38812 0.78935
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4781 1.4106 59.886 3.11e-16 ***
## A7 31.7573 8.1277 3.907 0.00208 **
## A64 -0.2980 0.2280 -1.307 0.21559
## A77 0.5294 1.3378 0.396 0.69926
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6123 on 12 degrees of freedom
## Multiple R-squared: 0.6503, Adjusted R-squared: 0.5628
## F-statistic: 7.437 on 3 and 12 DF, p-value: 0.004489
##
## A7 A64 A77
## 1.123108 1.117863 1.021665
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 42"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 1
## Medio 7 35 10 0
## Alto 0 0 118 14
## Excelente 0 0 13 117
##
## Overall Statistics
##
## Accuracy : 0.8651
## 95% CI : (0.8242, 0.8995)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7983
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78125 0.9722 0.8369 0.8864
## Specificity 0.99353 0.9443 0.9300 0.9378
## Pos Pred Value 0.92593 0.6731 0.8939 0.9000
## Neg Pred Value 0.97771 0.9965 0.8900 0.9289
## Prevalence 0.09384 0.1056 0.4135 0.3871
## Detection Rate 0.07331 0.1026 0.3460 0.3431
## Detection Prevalence 0.07918 0.1525 0.3871 0.3812
## Balanced Accuracy 0.88739 0.9582 0.8834 0.9121
## [1] "VARIABLES:A7,A64,A80,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.63853 -0.25997 0.01322 0.29230 0.89139
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 81.1259 1.6470 49.256 2.96e-14 ***
## A7 34.6720 6.5782 5.271 0.000264 ***
## A64 -0.2554 0.1828 -1.397 0.189948
## A80 1.9921 0.7136 2.792 0.017538 *
## A77 3.9567 1.6279 2.430 0.033381 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4893 on 11 degrees of freedom
## Multiple R-squared: 0.7953, Adjusted R-squared: 0.7208
## F-statistic: 10.68 on 4 and 11 DF, p-value: 0.0008741
##
## A7 A64 A80 A77
## 1.152135 1.125725 2.346620 2.369173
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 43"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 4 0 0
## Medio 8 41 15 0
## Alto 0 0 110 16
## Excelente 0 0 17 108
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7418
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 0.9111 0.7746 0.8710
## Specificity 0.98714 0.9223 0.9196 0.9217
## Pos Pred Value 0.84615 0.6406 0.8730 0.8640
## Neg Pred Value 0.97460 0.9856 0.8512 0.9259
## Prevalence 0.08798 0.1320 0.4164 0.3636
## Detection Rate 0.06452 0.1202 0.3226 0.3167
## Detection Prevalence 0.07625 0.1877 0.3695 0.3666
## Balanced Accuracy 0.86024 0.9167 0.8471 0.8963
## [1] "VARIABLES:A7,A64,A53,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.58861 -0.21181 -0.08127 0.28937 0.71139
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.28099 0.89943 95.929 < 2e-16 ***
## A7 27.09293 5.92544 4.572 0.00080 ***
## A64 -0.06343 0.18950 -0.335 0.74414
## A53 -5.55256 1.66027 -3.344 0.00654 **
## A9 -3.82394 2.56289 -1.492 0.16380
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4356 on 11 degrees of freedom
## Multiple R-squared: 0.8378, Adjusted R-squared: 0.7788
## F-statistic: 14.2 on 4 and 11 DF, p-value: 0.0002537
##
## A7 A64 A53 A9
## 1.179688 1.526592 1.499922 1.104273
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 44"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 1
## Medio 5 40 8 1
## Alto 0 0 112 23
## Excelente 0 0 17 112
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7485
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80000 0.9524 0.8175 0.8175
## Specificity 0.99051 0.9532 0.8873 0.9167
## Pos Pred Value 0.86957 0.7407 0.8296 0.8682
## Neg Pred Value 0.98428 0.9930 0.8786 0.8821
## Prevalence 0.07331 0.1232 0.4018 0.4018
## Detection Rate 0.05865 0.1173 0.3284 0.3284
## Detection Prevalence 0.06745 0.1584 0.3959 0.3783
## Balanced Accuracy 0.89525 0.9528 0.8524 0.8671
## [1] "VARIABLES:A7,A64,A41,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97124 -0.41033 0.08358 0.42657 0.72967
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.1067 1.4352 59.300 3.88e-15 ***
## A7 31.7803 8.1439 3.902 0.00247 **
## A64 -0.3066 0.2861 -1.072 0.30686
## A41 0.6288 2.0742 0.303 0.76744
## A9 -3.7005 3.6983 -1.001 0.33852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.616 on 11 degrees of freedom
## Multiple R-squared: 0.6755, Adjusted R-squared: 0.5576
## F-statistic: 5.726 on 4 and 11 DF, p-value: 0.009658
##
## A7 A64 A41 A9
## 1.114140 1.739638 1.675546 1.149645
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 45"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 2 0 0
## Medio 8 41 15 4
## Alto 0 0 122 28
## Excelente 0 0 6 98
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7243
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.68000 0.9535 0.8531 0.7538
## Specificity 0.99367 0.9094 0.8586 0.9716
## Pos Pred Value 0.89474 0.6029 0.8133 0.9423
## Neg Pred Value 0.97516 0.9927 0.8901 0.8650
## Prevalence 0.07331 0.1261 0.4194 0.3812
## Detection Rate 0.04985 0.1202 0.3578 0.2874
## Detection Prevalence 0.05572 0.1994 0.4399 0.3050
## Balanced Accuracy 0.83684 0.9314 0.8559 0.8627
## [1] "VARIABLES:A7,A64,A37,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68959 -0.31891 0.02216 0.37252 0.80056
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.59856 1.18539 72.211 4.46e-16 ***
## A7 29.98489 7.14984 4.194 0.0015 **
## A64 -0.23883 0.20084 -1.189 0.2594
## A37 -10.14550 4.70110 -2.158 0.0539 .
## A38 -0.01206 0.07049 -0.171 0.8673
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.536 on 11 degrees of freedom
## Multiple R-squared: 0.7544, Adjusted R-squared: 0.665
## F-statistic: 8.446 on 4 and 11 DF, p-value: 0.002282
##
## A7 A64 A37 A38
## 1.134334 1.132517 1.118777 1.099200
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 46"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 2 0 0
## Medio 8 43 16 0
## Alto 0 0 103 21
## Excelente 0 0 13 118
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7384
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.68000 0.9556 0.7803 0.8489
## Specificity 0.99367 0.9189 0.8995 0.9356
## Pos Pred Value 0.89474 0.6418 0.8306 0.9008
## Neg Pred Value 0.97516 0.9927 0.8664 0.9000
## Prevalence 0.07331 0.1320 0.3871 0.4076
## Detection Rate 0.04985 0.1261 0.3021 0.3460
## Detection Prevalence 0.05572 0.1965 0.3636 0.3842
## Balanced Accuracy 0.83684 0.9372 0.8399 0.8923
## [1] "VARIABLES:A7,A64,A41,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13290 -0.42791 0.05098 0.38411 0.78624
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.5089 1.5809 53.457 1.21e-14 ***
## A7 31.7777 8.4965 3.740 0.00327 **
## A64 -0.3086 0.3094 -0.998 0.33989
## A41 -0.1232 2.2909 -0.054 0.95809
## A77 0.5613 1.5180 0.370 0.71858
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6395 on 11 degrees of freedom
## Multiple R-squared: 0.6504, Adjusted R-squared: 0.5232
## F-statistic: 5.115 on 4 and 11 DF, p-value: 0.01414
##
## A7 A64 A41 A77
## 1.125359 1.887812 1.896855 1.206150
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 47"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 2 0 0
## Medio 6 40 13 2
## Alto 0 2 103 19
## Excelente 0 0 12 117
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7585
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80645 0.9091 0.8047 0.8478
## Specificity 0.99355 0.9293 0.9014 0.9409
## Pos Pred Value 0.92593 0.6557 0.8306 0.9070
## Neg Pred Value 0.98089 0.9857 0.8848 0.9009
## Prevalence 0.09091 0.1290 0.3754 0.4047
## Detection Rate 0.07331 0.1173 0.3021 0.3431
## Detection Prevalence 0.07918 0.1789 0.3636 0.3783
## Balanced Accuracy 0.90000 0.9192 0.8530 0.8944
## [1] "VARIABLES:A7,A64,A82,A53"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.79686 -0.21308 -0.06771 0.21024 0.62560
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.68679 0.83448 102.683 < 2e-16 ***
## A7 26.31124 6.08645 4.323 0.00121 **
## A64 -0.14227 0.22078 -0.644 0.53253
## A82 0.11444 0.09106 1.257 0.23488
## A53 -4.72927 1.79538 -2.634 0.02324 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4466 on 11 degrees of freedom
## Multiple R-squared: 0.8294, Adjusted R-squared: 0.7674
## F-statistic: 13.37 on 4 and 11 DF, p-value: 0.0003316
##
## A7 A64 A82 A53
## 1.183803 1.970920 1.363971 1.668196
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 48"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 3 0 0
## Medio 10 37 14 0
## Alto 0 0 113 21
## Excelente 0 0 13 101
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7397
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.74359 0.9250 0.8071 0.8279
## Specificity 0.99007 0.9203 0.8955 0.9406
## Pos Pred Value 0.90625 0.6066 0.8433 0.8860
## Neg Pred Value 0.96764 0.9893 0.8696 0.9075
## Prevalence 0.11437 0.1173 0.4106 0.3578
## Detection Rate 0.08504 0.1085 0.3314 0.2962
## Detection Prevalence 0.09384 0.1789 0.3930 0.3343
## Balanced Accuracy 0.86683 0.9226 0.8513 0.8843
## [1] "VARIABLES:A7,A64,A37,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68202 -0.29794 -0.00586 0.40977 0.80494
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.4351 1.0529 81.144 < 2e-16 ***
## A7 30.0093 7.1476 4.198 0.00149 **
## A64 -0.2288 0.2174 -1.052 0.31532
## A37 -10.3675 5.4328 -1.908 0.08278 .
## A9 0.5632 3.7960 0.148 0.88474
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5362 on 11 degrees of freedom
## Multiple R-squared: 0.7542, Adjusted R-squared: 0.6648
## F-statistic: 8.438 on 4 and 11 DF, p-value: 0.00229
##
## A7 A64 A37 A9
## 1.132883 1.326347 1.493141 1.598844
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 49"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 2 0 0
## Medio 8 39 9 0
## Alto 0 0 115 20
## Excelente 0 0 13 112
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7733
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.74194 0.9512 0.8394 0.8485
## Specificity 0.99355 0.9433 0.9020 0.9378
## Pos Pred Value 0.92000 0.6964 0.8519 0.8960
## Neg Pred Value 0.97468 0.9930 0.8932 0.9074
## Prevalence 0.09091 0.1202 0.4018 0.3871
## Detection Rate 0.06745 0.1144 0.3372 0.3284
## Detection Prevalence 0.07331 0.1642 0.3959 0.3666
## Balanced Accuracy 0.86774 0.9473 0.8707 0.8931
## [1] "VARIABLES:A7,A64,A41,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97124 -0.41033 0.08358 0.42657 0.72967
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.1067 1.4352 59.300 3.88e-15 ***
## A7 31.7803 8.1439 3.902 0.00247 **
## A64 -0.3066 0.2861 -1.072 0.30686
## A41 0.6288 2.0742 0.303 0.76744
## A9 -3.7005 3.6983 -1.001 0.33852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.616 on 11 degrees of freedom
## Multiple R-squared: 0.6755, Adjusted R-squared: 0.5576
## F-statistic: 5.726 on 4 and 11 DF, p-value: 0.009658
##
## A7 A64 A41 A9
## 1.114140 1.739638 1.675546 1.149645
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 50"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 3 0 0
## Medio 5 44 12 0
## Alto 0 0 104 25
## Excelente 0 0 7 117
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.776
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82759 0.9362 0.8455 0.8239
## Specificity 0.99038 0.9422 0.8853 0.9648
## Pos Pred Value 0.88889 0.7213 0.8062 0.9435
## Neg Pred Value 0.98408 0.9893 0.9104 0.8848
## Prevalence 0.08504 0.1378 0.3607 0.4164
## Detection Rate 0.07038 0.1290 0.3050 0.3431
## Detection Prevalence 0.07918 0.1789 0.3783 0.3636
## Balanced Accuracy 0.90899 0.9392 0.8654 0.8944
## [1] "VARIABLES:A7,A64,A12,A64,A6"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.02569 -0.30611 0.04986 0.27364 0.75952
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.0717 1.0307 82.534 < 2e-16 ***
## A7 34.0332 8.1412 4.180 0.00154 **
## A64 -0.4131 0.2334 -1.770 0.10443
## A12 1.9203 2.4289 0.791 0.44588
## A6 -0.4666 0.2531 -1.844 0.09228 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5619 on 11 degrees of freedom
## Multiple R-squared: 0.73, Adjusted R-squared: 0.6318
## F-statistic: 7.436 on 4 and 11 DF, p-value: 0.003738
##
## A7 A64 A12 A6
## 1.338028 1.391759 1.404803 1.323401
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 51"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 28 1 0 0
## Medio 8 42 14 1
## Alto 0 0 104 19
## Excelente 0 0 13 111
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.3842
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7616
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.77778 0.9767 0.7939 0.8473
## Specificity 0.99672 0.9228 0.9095 0.9381
## Pos Pred Value 0.96552 0.6462 0.8455 0.8952
## Neg Pred Value 0.97436 0.9964 0.8761 0.9078
## Prevalence 0.10557 0.1261 0.3842 0.3842
## Detection Rate 0.08211 0.1232 0.3050 0.3255
## Detection Prevalence 0.08504 0.1906 0.3607 0.3636
## Balanced Accuracy 0.88725 0.9498 0.8517 0.8927
## [1] "VARIABLES:A7,A64,A37,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68202 -0.29794 -0.00586 0.40977 0.80494
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.4351 1.0529 81.144 < 2e-16 ***
## A7 30.0093 7.1476 4.198 0.00149 **
## A64 -0.2288 0.2174 -1.052 0.31532
## A37 -10.3675 5.4328 -1.908 0.08278 .
## A9 0.5632 3.7960 0.148 0.88474
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5362 on 11 degrees of freedom
## Multiple R-squared: 0.7542, Adjusted R-squared: 0.6648
## F-statistic: 8.438 on 4 and 11 DF, p-value: 0.00229
##
## A7 A64 A37 A9
## 1.132883 1.326347 1.493141 1.598844
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 52"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 0 0 2
## Medio 8 39 11 1
## Alto 0 0 105 37
## Excelente 0 0 6 107
##
## Overall Statistics
##
## Accuracy : 0.8094
## 95% CI : (0.7636, 0.8497)
## No Information Rate : 0.4311
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.72
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75758 1.0000 0.8607 0.7279
## Specificity 0.99351 0.9338 0.8311 0.9691
## Pos Pred Value 0.92593 0.6610 0.7394 0.9469
## Neg Pred Value 0.97452 1.0000 0.9146 0.8246
## Prevalence 0.09677 0.1144 0.3578 0.4311
## Detection Rate 0.07331 0.1144 0.3079 0.3138
## Detection Prevalence 0.07918 0.1730 0.4164 0.3314
## Balanced Accuracy 0.87554 0.9669 0.8459 0.8485
## [1] "VARIABLES:A7,A64,A64,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.06260 -0.53189 0.07335 0.40315 0.71044
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.59002 1.24437 67.978 < 2e-16 ***
## A7 31.71318 8.11568 3.908 0.00208 **
## A64 -0.29485 0.22749 -1.296 0.21932
## A38 0.03090 0.07724 0.400 0.69611
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6123 on 12 degrees of freedom
## Multiple R-squared: 0.6504, Adjusted R-squared: 0.563
## F-statistic: 7.441 on 3 and 12 DF, p-value: 0.004481
##
## A7 A64 A38
## 1.120104 1.113599 1.011526
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 53"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 2 0 0
## Medio 2 35 19 0
## Alto 0 0 130 29
## Excelente 0 0 7 98
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4575
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.734
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90476 0.9459 0.8333 0.7717
## Specificity 0.99375 0.9309 0.8432 0.9673
## Pos Pred Value 0.90476 0.6250 0.8176 0.9333
## Neg Pred Value 0.99375 0.9930 0.8571 0.8771
## Prevalence 0.06158 0.1085 0.4575 0.3724
## Detection Rate 0.05572 0.1026 0.3812 0.2874
## Detection Prevalence 0.06158 0.1642 0.4663 0.3079
## Balanced Accuracy 0.94926 0.9384 0.8383 0.8695
## [1] "VARIABLES:A7,A64,A37,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68959 -0.31891 0.02216 0.37252 0.80056
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.59856 1.18539 72.211 4.46e-16 ***
## A7 29.98489 7.14984 4.194 0.0015 **
## A64 -0.23883 0.20084 -1.189 0.2594
## A37 -10.14550 4.70110 -2.158 0.0539 .
## A38 -0.01206 0.07049 -0.171 0.8673
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.536 on 11 degrees of freedom
## Multiple R-squared: 0.7544, Adjusted R-squared: 0.665
## F-statistic: 8.446 on 4 and 11 DF, p-value: 0.002282
##
## A7 A64 A37 A38
## 1.134334 1.132517 1.118777 1.099200
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 54"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 0 0 0
## Medio 8 45 15 0
## Alto 0 0 107 17
## Excelente 0 0 21 108
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.736
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 1.0000 0.7483 0.8640
## Specificity 1.00000 0.9223 0.9141 0.9028
## Pos Pred Value 1.00000 0.6618 0.8629 0.8372
## Neg Pred Value 0.97508 1.0000 0.8341 0.9198
## Prevalence 0.08211 0.1320 0.4194 0.3666
## Detection Rate 0.05865 0.1320 0.3138 0.3167
## Detection Prevalence 0.05865 0.1994 0.3636 0.3783
## Balanced Accuracy 0.85714 0.9611 0.8312 0.8834
## [1] "VARIABLES:A7,A64,A6,A24"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.37508 -0.18545 -0.07095 0.11648 0.54901
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.6283 1.0382 86.330 < 2e-16 ***
## A7 26.8059 4.5543 5.886 0.000105 ***
## A64 -0.4597 0.1159 -3.966 0.002210 **
## A6 -0.4303 0.1290 -3.336 0.006639 **
## A24 -1.1095 0.2065 -5.372 0.000226 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3035 on 11 degrees of freedom
## Multiple R-squared: 0.9213, Adjusted R-squared: 0.8926
## F-statistic: 32.18 on 4 and 11 DF, p-value: 5.152e-06
##
## A7 A64 A6 A24
## 1.435801 1.176464 1.178775 1.191733
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 55"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 5 24 6 1
## Alto 0 11 118 18
## Excelente 0 0 7 125
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.78
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.83333 0.66667 0.9008 0.8681
## Specificity 0.99678 0.96066 0.8619 0.9645
## Pos Pred Value 0.96154 0.66667 0.8027 0.9470
## Neg Pred Value 0.98413 0.96066 0.9330 0.9091
## Prevalence 0.08798 0.10557 0.3842 0.4223
## Detection Rate 0.07331 0.07038 0.3460 0.3666
## Detection Prevalence 0.07625 0.10557 0.4311 0.3871
## Balanced Accuracy 0.91506 0.81366 0.8813 0.9163
## [1] "VARIABLES:A7,A7,A41,A10,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.1190 -0.3617 0.0912 0.2862 0.9321
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.99477 1.37437 61.115 2.79e-15 ***
## A7 26.51755 9.59413 2.764 0.0184 *
## A41 2.21600 1.82758 1.213 0.2507
## A10 2.78621 2.07404 1.343 0.2062
## A77 0.06716 1.40174 0.048 0.9626
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.619 on 11 degrees of freedom
## Multiple R-squared: 0.6725, Adjusted R-squared: 0.5534
## F-statistic: 5.646 on 4 and 11 DF, p-value: 0.01014
##
## A7 A41 A10 A77
## 1.531711 1.288587 1.504890 1.097826
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 56"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 2 1 2
## Medio 2 40 15 0
## Alto 0 3 112 19
## Excelente 0 0 17 110
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7305
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90000 0.8889 0.7724 0.8397
## Specificity 0.98442 0.9426 0.8878 0.9190
## Pos Pred Value 0.78261 0.7018 0.8358 0.8661
## Neg Pred Value 0.99371 0.9824 0.8406 0.9019
## Prevalence 0.05865 0.1320 0.4252 0.3842
## Detection Rate 0.05279 0.1173 0.3284 0.3226
## Detection Prevalence 0.06745 0.1672 0.3930 0.3724
## Balanced Accuracy 0.94221 0.9157 0.8301 0.8794
## [1] "VARIABLES:A7,A64,A33,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9934 -0.3339 0.1852 0.3171 0.6730
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.3980 1.4052 61.486 2.61e-15 ***
## A7 28.7138 8.0044 3.587 0.00426 **
## A64 -0.4727 0.2417 -1.956 0.07637 .
## A33 -11.1282 8.7534 -1.271 0.22985
## A9 -2.7626 3.4414 -0.803 0.43911
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5776 on 11 degrees of freedom
## Multiple R-squared: 0.7147, Adjusted R-squared: 0.611
## F-statistic: 6.89 on 4 and 11 DF, p-value: 0.004974
##
## A7 A64 A33 A9
## 1.224205 1.412681 1.284629 1.132299
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 57"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 2 0 0
## Medio 7 41 12 0
## Alto 0 0 103 15
## Excelente 0 0 11 126
##
## Overall Statistics
##
## Accuracy : 0.8622
## 95% CI : (0.821, 0.8969)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7964
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.77419 0.9535 0.8175 0.8936
## Specificity 0.99355 0.9362 0.9302 0.9450
## Pos Pred Value 0.92308 0.6833 0.8729 0.9197
## Neg Pred Value 0.97778 0.9929 0.8969 0.9265
## Prevalence 0.09091 0.1261 0.3695 0.4135
## Detection Rate 0.07038 0.1202 0.3021 0.3695
## Detection Prevalence 0.07625 0.1760 0.3460 0.4018
## Balanced Accuracy 0.88387 0.9449 0.8738 0.9193
## [1] "VARIABLES:A7,A64,A64,A44"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84955 -0.17265 -0.09992 0.36308 0.78085
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.7604 0.9307 91.074 < 2e-16 ***
## A7 28.9180 7.0591 4.097 0.00148 **
## A64 -0.4278 0.2060 -2.077 0.05999 .
## A44 0.7611 0.3615 2.105 0.05701 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5267 on 12 degrees of freedom
## Multiple R-squared: 0.7413, Adjusted R-squared: 0.6766
## F-statistic: 11.46 on 3 and 12 DF, p-value: 0.000776
##
## A7 A64 A44
## 1.145134 1.233825 1.114409
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 58"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 0
## Medio 6 50 15 0
## Alto 0 0 109 19
## Excelente 0 0 15 105
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7506
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76000 0.9434 0.7842 0.8468
## Specificity 0.99051 0.9271 0.9059 0.9309
## Pos Pred Value 0.86364 0.7042 0.8516 0.8750
## Neg Pred Value 0.98119 0.9889 0.8592 0.9140
## Prevalence 0.07331 0.1554 0.4076 0.3636
## Detection Rate 0.05572 0.1466 0.3196 0.3079
## Detection Prevalence 0.06452 0.2082 0.3754 0.3519
## Balanced Accuracy 0.87525 0.9352 0.8451 0.8888
## [1] "VARIABLES:A7,A64,A36,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81566 -0.38455 -0.02778 0.49495 0.60408
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.4675 1.5903 54.372 1e-14 ***
## A7 25.6422 9.8006 2.616 0.024 *
## A64 -0.2477 0.2506 -0.988 0.344
## A36 -1.0266 0.9932 -1.034 0.324
## A9 -2.6147 3.5699 -0.732 0.479
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5906 on 11 degrees of freedom
## Multiple R-squared: 0.7018, Adjusted R-squared: 0.5934
## F-statistic: 6.472 on 4 and 11 DF, p-value: 0.006258
##
## A7 A64 A36 A9
## 1.755579 1.452064 2.076374 1.165528
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 59"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 3 0 0
## Medio 5 40 11 2
## Alto 0 0 115 32
## Excelente 0 0 3 101
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7604
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.85294 0.9302 0.8915 0.7481
## Specificity 0.99023 0.9396 0.8491 0.9854
## Pos Pred Value 0.90625 0.6897 0.7823 0.9712
## Neg Pred Value 0.98382 0.9894 0.9278 0.8565
## Prevalence 0.09971 0.1261 0.3783 0.3959
## Detection Rate 0.08504 0.1173 0.3372 0.2962
## Detection Prevalence 0.09384 0.1701 0.4311 0.3050
## Balanced Accuracy 0.92158 0.9349 0.8703 0.8668
## [1] "VARIABLES:A7,A64,A37,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68959 -0.31891 0.02216 0.37252 0.80056
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.59856 1.18539 72.211 4.46e-16 ***
## A7 29.98489 7.14984 4.194 0.0015 **
## A64 -0.23883 0.20084 -1.189 0.2594
## A37 -10.14550 4.70110 -2.158 0.0539 .
## A38 -0.01206 0.07049 -0.171 0.8673
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.536 on 11 degrees of freedom
## Multiple R-squared: 0.7544, Adjusted R-squared: 0.665
## F-statistic: 8.446 on 4 and 11 DF, p-value: 0.002282
##
## A7 A64 A37 A38
## 1.134334 1.132517 1.118777 1.099200
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 60"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 0 1 1
## Medio 9 42 12 1
## Alto 0 0 111 14
## Excelente 0 0 14 117
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7736
##
## Mcnemar's Test P-Value : 0.0005223
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.67857 1.0000 0.8043 0.8797
## Specificity 0.99361 0.9264 0.9310 0.9327
## Pos Pred Value 0.90476 0.6563 0.8880 0.8931
## Neg Pred Value 0.97188 1.0000 0.8750 0.9238
## Prevalence 0.08211 0.1232 0.4047 0.3900
## Detection Rate 0.05572 0.1232 0.3255 0.3431
## Detection Prevalence 0.06158 0.1877 0.3666 0.3842
## Balanced Accuracy 0.83609 0.9632 0.8677 0.9062
## [1] "VARIABLES:A7,A64,A64,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 61"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 10 50 12 0
## Alto 0 0 109 18
## Excelente 0 1 10 105
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.3842
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7803
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 0.9615 0.8321 0.8537
## Specificity 0.99673 0.9239 0.9143 0.9495
## Pos Pred Value 0.96154 0.6944 0.8583 0.9052
## Neg Pred Value 0.96825 0.9926 0.8972 0.9200
## Prevalence 0.10264 0.1525 0.3842 0.3607
## Detection Rate 0.07331 0.1466 0.3196 0.3079
## Detection Prevalence 0.07625 0.2111 0.3724 0.3402
## Balanced Accuracy 0.85551 0.9427 0.8732 0.9016
## [1] "VARIABLES:A7,A64,A37,A83,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64253 -0.32025 0.00932 0.26428 0.94132
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.0461 1.2568 67.670 1.21e-14 ***
## A7 31.4295 7.7173 4.073 0.00224 **
## A64 -0.1873 0.2339 -0.801 0.44193
## A37 -11.5836 5.9367 -1.951 0.07959 .
## A83 0.5657 0.9245 0.612 0.55426
## A9 1.5696 4.2407 0.370 0.71901
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5521 on 10 degrees of freedom
## Multiple R-squared: 0.7631, Adjusted R-squared: 0.6446
## F-statistic: 6.442 on 5 and 10 DF, p-value: 0.0063
##
## A7 A64 A37 A83 A9
## 1.245551 1.447859 1.681589 1.339636 1.881937
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 62"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 3 0 0
## Medio 4 39 13 0
## Alto 0 5 108 29
## Excelente 0 0 9 110
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7247
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.84000 0.8298 0.8308 0.7914
## Specificity 0.99051 0.9422 0.8389 0.9554
## Pos Pred Value 0.87500 0.6964 0.7606 0.9244
## Neg Pred Value 0.98738 0.9719 0.8894 0.8694
## Prevalence 0.07331 0.1378 0.3812 0.4076
## Detection Rate 0.06158 0.1144 0.3167 0.3226
## Detection Prevalence 0.07038 0.1642 0.4164 0.3490
## Balanced Accuracy 0.91525 0.8860 0.8348 0.8734
## [1] "VARIABLES:A7,A7,A64,A62,A84"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97127 -0.34427 0.09398 0.27450 0.79582
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.25460 2.22313 39.698 3.14e-13 ***
## A7 21.69249 10.61934 2.043 0.0658 .
## A64 0.07486 0.31899 0.235 0.8188
## A62 -1.72210 2.01724 -0.854 0.4115
## A84 -8.10685 4.39230 -1.846 0.0920 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.56 on 11 degrees of freedom
## Multiple R-squared: 0.7319, Adjusted R-squared: 0.6344
## F-statistic: 7.507 on 4 and 11 DF, p-value: 0.003604
##
## A7 A64 A62 A84
## 2.292586 2.617368 2.009589 2.920779
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 63"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 7 47 13 0
## Alto 0 0 116 19
## Excelente 0 0 10 103
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.786
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78125 0.9792 0.8345 0.8443
## Specificity 0.99676 0.9317 0.9059 0.9543
## Pos Pred Value 0.96154 0.7015 0.8593 0.9115
## Neg Pred Value 0.97778 0.9964 0.8883 0.9167
## Prevalence 0.09384 0.1408 0.4076 0.3578
## Detection Rate 0.07331 0.1378 0.3402 0.3021
## Detection Prevalence 0.07625 0.1965 0.3959 0.3314
## Balanced Accuracy 0.88901 0.9555 0.8702 0.8993
## [1] "VARIABLES:A7,A64,A7,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 64"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 0
## Medio 4 37 13 2
## Alto 0 0 118 31
## Excelente 0 0 4 110
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.748
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82609 0.9250 0.8741 0.7692
## Specificity 0.99057 0.9369 0.8495 0.9798
## Pos Pred Value 0.86364 0.6607 0.7919 0.9649
## Neg Pred Value 0.98746 0.9895 0.9115 0.8546
## Prevalence 0.06745 0.1173 0.3959 0.4194
## Detection Rate 0.05572 0.1085 0.3460 0.3226
## Detection Prevalence 0.06452 0.1642 0.4370 0.3343
## Balanced Accuracy 0.90833 0.9309 0.8618 0.8745
## [1] "VARIABLES:A7,A64,A36,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85906 -0.39283 -0.09191 0.50578 0.61586
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.11470 1.79495 47.976 3.96e-14 ***
## A7 24.75370 9.98842 2.478 0.0307 *
## A64 -0.18995 0.24167 -0.786 0.4485
## A36 -1.16179 0.99866 -1.163 0.2693
## A38 0.01724 0.07703 0.224 0.8270
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6034 on 11 degrees of freedom
## Multiple R-squared: 0.6887, Adjusted R-squared: 0.5755
## F-statistic: 6.083 on 4 and 11 DF, p-value: 0.007813
##
## A7 A64 A36 A38
## 1.746648 1.293712 2.010721 1.035612
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 65"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 15 1 0 0
## Medio 6 39 3 0
## Alto 0 16 126 28
## Excelente 0 0 11 96
##
## Overall Statistics
##
## Accuracy : 0.8094
## 95% CI : (0.7636, 0.8497)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7091
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 0.6964 0.9000 0.7742
## Specificity 0.99687 0.9684 0.7811 0.9493
## Pos Pred Value 0.93750 0.8125 0.7412 0.8972
## Neg Pred Value 0.98154 0.9420 0.9181 0.8803
## Prevalence 0.06158 0.1642 0.4106 0.3636
## Detection Rate 0.04399 0.1144 0.3695 0.2815
## Detection Prevalence 0.04692 0.1408 0.4985 0.3138
## Balanced Accuracy 0.85558 0.8324 0.8405 0.8618
## [1] "VARIABLES:A7,A7,A64,A76"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9732 -0.4607 0.0558 0.4420 0.7881
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.2689 1.2499 67.420 < 2e-16 ***
## A7 33.5543 8.2874 4.049 0.00161 **
## A64 -0.1573 0.2726 -0.577 0.57446
## A76 0.2001 0.2352 0.851 0.41163
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5985 on 12 degrees of freedom
## Multiple R-squared: 0.6659, Adjusted R-squared: 0.5823
## F-statistic: 7.971 on 3 and 12 DF, p-value: 0.003447
##
## A7 A64 A76
## 1.222119 1.672881 1.512970
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 66"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 6 0 0
## Medio 6 47 13 1
## Alto 0 0 92 16
## Excelente 0 0 11 123
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7753
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.81250 0.8868 0.7931 0.8786
## Specificity 0.98058 0.9306 0.9289 0.9453
## Pos Pred Value 0.81250 0.7015 0.8519 0.9179
## Neg Pred Value 0.98058 0.9781 0.8970 0.9179
## Prevalence 0.09384 0.1554 0.3402 0.4106
## Detection Rate 0.07625 0.1378 0.2698 0.3607
## Detection Prevalence 0.09384 0.1965 0.3167 0.3930
## Balanced Accuracy 0.89654 0.9087 0.8610 0.9119
## [1] "VARIABLES:A7,A64,A82,A25"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73418 -0.17386 -0.04525 0.21231 0.60238
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.21502 1.43512 62.165 2.31e-15 ***
## A7 26.15531 5.42304 4.823 0.000533 ***
## A64 -0.45950 0.16408 -2.800 0.017262 *
## A82 0.03835 0.08940 0.429 0.676195
## A25 -1.24181 0.36714 -3.382 0.006117 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3993 on 11 degrees of freedom
## Multiple R-squared: 0.8637, Adjusted R-squared: 0.8141
## F-statistic: 17.42 on 4 and 11 DF, p-value: 1e-04
##
## A7 A64 A82 A25
## 1.175654 1.361758 1.644471 1.454023
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 67"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 1 0 0
## Medio 10 39 13 0
## Alto 0 0 99 18
## Excelente 0 0 15 123
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.753
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.69697 0.9750 0.7795 0.8723
## Specificity 0.99675 0.9236 0.9159 0.9250
## Pos Pred Value 0.95833 0.6290 0.8462 0.8913
## Neg Pred Value 0.96845 0.9964 0.8750 0.9113
## Prevalence 0.09677 0.1173 0.3724 0.4135
## Detection Rate 0.06745 0.1144 0.2903 0.3607
## Detection Prevalence 0.07038 0.1818 0.3431 0.4047
## Balanced Accuracy 0.84686 0.9493 0.8477 0.8987
## [1] "VARIABLES:A7,A64,A6,A28"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.96480 -0.42076 0.06249 0.37590 0.60177
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.4142 1.1087 77.037 < 2e-16 ***
## A7 33.5994 7.9530 4.225 0.00142 **
## A64 -0.4273 0.2245 -1.904 0.08345 .
## A6 -0.3570 0.2373 -1.505 0.16054
## A28 -2.6722 2.5313 -1.056 0.31375
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5505 on 11 degrees of freedom
## Multiple R-squared: 0.7409, Adjusted R-squared: 0.6467
## F-statistic: 7.864 on 4 and 11 DF, p-value: 0.003015
##
## A7 A64 A6 A28
## 1.330629 1.341037 1.212161 1.246439
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 68"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 12 37 11 0
## Alto 0 0 106 18
## Excelente 0 0 17 114
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7458
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.67568 0.9737 0.7910 0.8636
## Specificity 0.99671 0.9241 0.9130 0.9187
## Pos Pred Value 0.96154 0.6167 0.8548 0.8702
## Neg Pred Value 0.96190 0.9964 0.8710 0.9143
## Prevalence 0.10850 0.1114 0.3930 0.3871
## Detection Rate 0.07331 0.1085 0.3109 0.3343
## Detection Prevalence 0.07625 0.1760 0.3636 0.3842
## Balanced Accuracy 0.83619 0.9489 0.8520 0.8911
## [1] "VARIABLES:A56,A64,A41,A7"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.99056 -0.32494 0.07533 0.42993 0.70895
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.5878 2.2307 38.817 4.02e-13 ***
## A56 -0.5272 0.5014 -1.052 0.3156
## A64 -0.2547 0.2836 -0.898 0.3884
## A41 0.3084 2.0246 0.152 0.8817
## A7 22.6028 11.6716 1.937 0.0789 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6134 on 11 degrees of freedom
## Multiple R-squared: 0.6783, Adjusted R-squared: 0.5614
## F-statistic: 5.8 on 4 and 11 DF, p-value: 0.009238
##
## A56 A64 A41 A7
## 2.235012 1.724958 1.610296 2.308359
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 69"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 0 0 0
## Medio 9 35 3 1
## Alto 0 14 110 22
## Excelente 0 0 10 117
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7408
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.68966 0.7143 0.8943 0.8357
## Specificity 1.00000 0.9555 0.8349 0.9502
## Pos Pred Value 1.00000 0.7292 0.7534 0.9213
## Neg Pred Value 0.97196 0.9522 0.9333 0.8925
## Prevalence 0.08504 0.1437 0.3607 0.4106
## Detection Rate 0.05865 0.1026 0.3226 0.3431
## Detection Prevalence 0.05865 0.1408 0.4282 0.3724
## Balanced Accuracy 0.84483 0.8349 0.8646 0.8930
## [1] "VARIABLES:A7,A7,A36,A10,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.86729 -0.31410 0.03463 0.29091 0.89216
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.8182 1.6027 54.170 1.05e-14 ***
## A7 20.0378 10.5762 1.895 0.0847 .
## A36 -1.5110 0.8906 -1.697 0.1179
## A10 2.1709 1.8209 1.192 0.2583
## A9 -1.7374 3.3067 -0.525 0.6097
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5799 on 11 degrees of freedom
## Multiple R-squared: 0.7125, Adjusted R-squared: 0.6079
## F-statistic: 6.814 on 4 and 11 DF, p-value: 0.005184
##
## A7 A36 A10 A9
## 2.120330 1.731416 1.321347 1.037120
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 70"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 2 0 0
## Medio 6 39 18 0
## Alto 0 0 110 22
## Excelente 0 0 13 105
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7374
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.81250 0.9512 0.7801 0.8268
## Specificity 0.99353 0.9200 0.8900 0.9393
## Pos Pred Value 0.92857 0.6190 0.8333 0.8898
## Neg Pred Value 0.98083 0.9928 0.8517 0.9013
## Prevalence 0.09384 0.1202 0.4135 0.3724
## Detection Rate 0.07625 0.1144 0.3226 0.3079
## Detection Prevalence 0.08211 0.1848 0.3871 0.3460
## Balanced Accuracy 0.90301 0.9356 0.8351 0.8830
## [1] "VARIABLES:A7,A64,A37,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.69418 -0.33114 0.03821 0.20932 0.93578
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.8946 1.2146 69.896 6.38e-16 ***
## A7 30.6078 6.9406 4.410 0.00105 **
## A64 -0.2499 0.1953 -1.280 0.22697
## A37 -10.4400 4.4364 -2.353 0.03827 *
## A77 0.9259 1.1520 0.804 0.43854
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5216 on 11 degrees of freedom
## Multiple R-squared: 0.7674, Adjusted R-squared: 0.6828
## F-statistic: 9.072 on 4 and 11 DF, p-value: 0.001715
##
## A7 A64 A37 A77
## 1.128698 1.130270 1.052054 1.044006
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 71"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 15 0 0 0
## Medio 10 52 13 1
## Alto 0 0 115 14
## Excelente 0 0 17 104
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7621
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.60000 1.0000 0.7931 0.8739
## Specificity 1.00000 0.9170 0.9286 0.9234
## Pos Pred Value 1.00000 0.6842 0.8915 0.8595
## Neg Pred Value 0.96933 1.0000 0.8585 0.9318
## Prevalence 0.07331 0.1525 0.4252 0.3490
## Detection Rate 0.04399 0.1525 0.3372 0.3050
## Detection Prevalence 0.04399 0.2229 0.3783 0.3548
## Balanced Accuracy 0.80000 0.9585 0.8608 0.8987
## [1] "VARIABLES:A7,A64,A36,A3,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81819 -0.38874 -0.02812 0.48907 0.57702
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.4903 1.7004 50.864 2.09e-13 ***
## A7 25.2213 11.9823 2.105 0.0616 .
## A64 -0.2535 0.2761 -0.918 0.3802
## A36 -1.0388 1.0567 -0.983 0.3488
## A3 0.2393 3.5030 0.068 0.9469
## A9 -2.6140 3.7433 -0.698 0.5009
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6193 on 10 degrees of freedom
## Multiple R-squared: 0.7019, Adjusted R-squared: 0.5529
## F-statistic: 4.71 on 5 and 10 DF, p-value: 0.018
##
## A7 A64 A36 A3 A9
## 2.386766 1.603615 2.137687 1.485489 1.165536
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 72"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 1 0 0
## Medio 7 32 13 1
## Alto 0 0 113 18
## Excelente 0 0 13 121
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.765
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75862 0.96970 0.8129 0.8643
## Specificity 0.99679 0.93182 0.9109 0.9353
## Pos Pred Value 0.95652 0.60377 0.8626 0.9030
## Neg Pred Value 0.97799 0.99653 0.8762 0.9082
## Prevalence 0.08504 0.09677 0.4076 0.4106
## Detection Rate 0.06452 0.09384 0.3314 0.3548
## Detection Prevalence 0.06745 0.15543 0.3842 0.3930
## Balanced Accuracy 0.87771 0.95076 0.8619 0.8998
## [1] "VARIABLES:A7,A64,A64,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13108 -0.43106 0.04603 0.38812 0.78935
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4781 1.4106 59.886 3.11e-16 ***
## A7 31.7573 8.1277 3.907 0.00208 **
## A64 -0.2980 0.2280 -1.307 0.21559
## A77 0.5294 1.3378 0.396 0.69926
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6123 on 12 degrees of freedom
## Multiple R-squared: 0.6503, Adjusted R-squared: 0.5628
## F-statistic: 7.437 on 3 and 12 DF, p-value: 0.004489
##
## A7 A64 A77
## 1.123108 1.117863 1.021665
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 73"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 3 1 0
## Medio 5 50 18 0
## Alto 0 0 101 18
## Excelente 0 0 17 107
##
## Overall Statistics
##
## Accuracy : 0.8182
## 95% CI : (0.7731, 0.8577)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7356
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80769 0.9434 0.7372 0.8560
## Specificity 0.98730 0.9201 0.9118 0.9213
## Pos Pred Value 0.84000 0.6849 0.8487 0.8629
## Neg Pred Value 0.98418 0.9888 0.8378 0.9171
## Prevalence 0.07625 0.1554 0.4018 0.3666
## Detection Rate 0.06158 0.1466 0.2962 0.3138
## Detection Prevalence 0.07331 0.2141 0.3490 0.3636
## Balanced Accuracy 0.89750 0.9318 0.8245 0.8886
## [1] "VARIABLES:A7,A64,A64,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 74"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 1 0 2
## Medio 7 40 15 0
## Alto 0 0 106 31
## Excelente 0 0 7 103
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7318
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80556 0.9756 0.8281 0.7574
## Specificity 0.99016 0.9267 0.8545 0.9659
## Pos Pred Value 0.90625 0.6452 0.7737 0.9364
## Neg Pred Value 0.97735 0.9964 0.8922 0.8571
## Prevalence 0.10557 0.1202 0.3754 0.3988
## Detection Rate 0.08504 0.1173 0.3109 0.3021
## Detection Prevalence 0.09384 0.1818 0.4018 0.3226
## Balanced Accuracy 0.89786 0.9511 0.8413 0.8616
## [1] "VARIABLES:A7,A64,A41,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.02228 -0.42069 0.04795 0.38317 0.77293
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.97057 2.02002 41.569 1.9e-13 ***
## A7 31.90474 8.42971 3.785 0.00302 **
## A64 -0.21200 0.31442 -0.674 0.51407
## A41 1.02625 2.57477 0.399 0.69783
## A38 0.05376 0.09851 0.546 0.59613
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6349 on 11 degrees of freedom
## Multiple R-squared: 0.6553, Adjusted R-squared: 0.53
## F-statistic: 5.229 on 4 and 11 DF, p-value: 0.01315
##
## A7 A64 A41 A38
## 1.123756 1.978154 2.430631 1.530222
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 75"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 0 0 0
## Medio 3 28 5 0
## Alto 0 18 115 36
## Excelente 0 0 10 102
##
## Overall Statistics
##
## Accuracy : 0.7889
## 95% CI : (0.7416, 0.831)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6793
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.88889 0.60870 0.8846 0.7391
## Specificity 1.00000 0.97288 0.7441 0.9507
## Pos Pred Value 1.00000 0.77778 0.6805 0.9107
## Neg Pred Value 0.99054 0.94098 0.9128 0.8428
## Prevalence 0.07918 0.13490 0.3812 0.4047
## Detection Rate 0.07038 0.08211 0.3372 0.2991
## Detection Prevalence 0.07038 0.10557 0.4956 0.3284
## Balanced Accuracy 0.94444 0.79079 0.8143 0.8449
## [1] "VARIABLES:A7,A7,A64,A76"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9732 -0.4607 0.0558 0.4420 0.7881
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.2689 1.2499 67.420 < 2e-16 ***
## A7 33.5543 8.2874 4.049 0.00161 **
## A64 -0.1573 0.2726 -0.577 0.57446
## A76 0.2001 0.2352 0.851 0.41163
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5985 on 12 degrees of freedom
## Multiple R-squared: 0.6659, Adjusted R-squared: 0.5823
## F-statistic: 7.971 on 3 and 12 DF, p-value: 0.003447
##
## A7 A64 A76
## 1.222119 1.672881 1.512970
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 76"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 1 0 0
## Medio 10 41 14 0
## Alto 0 0 108 19
## Excelente 0 0 16 103
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7453
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.74359 0.9762 0.7826 0.8443
## Specificity 0.99669 0.9197 0.9064 0.9269
## Pos Pred Value 0.96667 0.6308 0.8504 0.8655
## Neg Pred Value 0.96785 0.9964 0.8598 0.9144
## Prevalence 0.11437 0.1232 0.4047 0.3578
## Detection Rate 0.08504 0.1202 0.3167 0.3021
## Detection Prevalence 0.08798 0.1906 0.3724 0.3490
## Balanced Accuracy 0.87014 0.9480 0.8445 0.8856
## [1] "VARIABLES:A7,A64,A6,A3"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0877 -0.3075 0.1048 0.3268 0.7264
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.9164 1.0132 83.812 < 2e-16 ***
## A7 33.5700 8.8755 3.782 0.00303 **
## A64 -0.3936 0.2400 -1.640 0.12918
## A6 -0.4575 0.2635 -1.736 0.11037
## A3 1.9077 3.4569 0.552 0.59209
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5699 on 11 degrees of freedom
## Multiple R-squared: 0.7224, Adjusted R-squared: 0.6214
## F-statistic: 7.155 on 4 and 11 DF, p-value: 0.004323
##
## A7 A64 A6 A3
## 1.546438 1.430241 1.394996 1.708379
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 77"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 1 0 0
## Medio 7 36 16 0
## Alto 0 0 103 19
## Excelente 0 0 21 112
##
## Overall Statistics
##
## Accuracy : 0.8123
## 95% CI : (0.7668, 0.8524)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7227
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78788 0.9730 0.7357 0.8550
## Specificity 0.99675 0.9243 0.9055 0.9000
## Pos Pred Value 0.96296 0.6102 0.8443 0.8421
## Neg Pred Value 0.97771 0.9965 0.8311 0.9087
## Prevalence 0.09677 0.1085 0.4106 0.3842
## Detection Rate 0.07625 0.1056 0.3021 0.3284
## Detection Prevalence 0.07918 0.1730 0.3578 0.3900
## Balanced Accuracy 0.89232 0.9487 0.8206 0.8775
## [1] "VARIABLES:A7,A64,A6,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.87181 -0.31718 -0.08825 0.37580 0.60332
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.5464 1.0359 82.580 < 2e-16 ***
## A7 36.9181 7.3867 4.998 0.000404 ***
## A64 -0.4264 0.2061 -2.069 0.062876 .
## A6 -0.4686 0.2278 -2.057 0.064152 .
## A9 -4.7672 3.1537 -1.512 0.158808
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5257 on 11 degrees of freedom
## Multiple R-squared: 0.7637, Adjusted R-squared: 0.6778
## F-statistic: 8.89 on 4 and 11 DF, p-value: 0.001861
##
## A7 A64 A6 A9
## 1.258796 1.239613 1.225244 1.148083
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 78"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 5 0 0
## Medio 4 44 13 1
## Alto 0 0 116 21
## Excelente 0 0 8 106
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7759
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.85185 0.8980 0.8467 0.8281
## Specificity 0.98408 0.9384 0.8971 0.9624
## Pos Pred Value 0.82143 0.7097 0.8467 0.9298
## Neg Pred Value 0.98722 0.9821 0.8971 0.9031
## Prevalence 0.07918 0.1437 0.4018 0.3754
## Detection Rate 0.06745 0.1290 0.3402 0.3109
## Detection Prevalence 0.08211 0.1818 0.4018 0.3343
## Balanced Accuracy 0.91796 0.9182 0.8719 0.8953
## [1] "VARIABLES:A7,A64,A25,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74558 -0.18833 0.00015 0.24524 0.61690
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.4597 1.3251 67.513 9.34e-16 ***
## A7 26.2744 5.5073 4.771 0.00058 ***
## A64 -0.4360 0.1569 -2.778 0.01797 *
## A25 -1.3118 0.3389 -3.870 0.00261 **
## A9 -0.2136 2.5119 -0.085 0.93376
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4025 on 11 degrees of freedom
## Multiple R-squared: 0.8615, Adjusted R-squared: 0.8111
## F-statistic: 17.1 on 4 and 11 DF, p-value: 0.000109
##
## A7 A64 A25 A9
## 1.193305 1.226119 1.219680 1.242083
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 79"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 1 0 1
## Medio 7 45 14 0
## Alto 0 0 99 16
## Excelente 0 0 16 116
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.39
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7654
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78788 0.9783 0.7674 0.8722
## Specificity 0.99351 0.9288 0.9245 0.9231
## Pos Pred Value 0.92857 0.6818 0.8609 0.8788
## Neg Pred Value 0.97764 0.9964 0.8673 0.9187
## Prevalence 0.09677 0.1349 0.3783 0.3900
## Detection Rate 0.07625 0.1320 0.2903 0.3402
## Detection Prevalence 0.08211 0.1935 0.3372 0.3871
## Balanced Accuracy 0.89069 0.9535 0.8460 0.8976
## [1] "VARIABLES:A7,A64,A41,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97124 -0.41033 0.08358 0.42657 0.72967
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.1067 1.4352 59.300 3.88e-15 ***
## A7 31.7803 8.1439 3.902 0.00247 **
## A64 -0.3066 0.2861 -1.072 0.30686
## A41 0.6288 2.0742 0.303 0.76744
## A9 -3.7005 3.6983 -1.001 0.33852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.616 on 11 degrees of freedom
## Multiple R-squared: 0.6755, Adjusted R-squared: 0.5576
## F-statistic: 5.726 on 4 and 11 DF, p-value: 0.009658
##
## A7 A64 A41 A9
## 1.114140 1.739638 1.675546 1.149645
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 80"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 0 0 0
## Medio 7 50 18 0
## Alto 0 0 105 17
## Excelente 0 0 21 101
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7312
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75862 1.0000 0.7292 0.8559
## Specificity 1.00000 0.9141 0.9137 0.9058
## Pos Pred Value 1.00000 0.6667 0.8607 0.8279
## Neg Pred Value 0.97806 1.0000 0.8219 0.9224
## Prevalence 0.08504 0.1466 0.4223 0.3460
## Detection Rate 0.06452 0.1466 0.3079 0.2962
## Detection Prevalence 0.06452 0.2199 0.3578 0.3578
## Balanced Accuracy 0.87931 0.9570 0.8214 0.8809
## [1] "VARIABLES:A7,A64,A6,A3"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0877 -0.3075 0.1048 0.3268 0.7264
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.9164 1.0132 83.812 < 2e-16 ***
## A7 33.5700 8.8755 3.782 0.00303 **
## A64 -0.3936 0.2400 -1.640 0.12918
## A6 -0.4575 0.2635 -1.736 0.11037
## A3 1.9077 3.4569 0.552 0.59209
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5699 on 11 degrees of freedom
## Multiple R-squared: 0.7224, Adjusted R-squared: 0.6214
## F-statistic: 7.155 on 4 and 11 DF, p-value: 0.004323
##
## A7 A64 A6 A3
## 1.546438 1.430241 1.394996 1.708379
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 81"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 15 4 0 0
## Medio 4 46 21 2
## Alto 0 0 94 22
## Excelente 0 0 15 118
##
## Overall Statistics
##
## Accuracy : 0.8006
## 95% CI : (0.7542, 0.8417)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7039
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78947 0.9200 0.7231 0.8310
## Specificity 0.98758 0.9072 0.8957 0.9246
## Pos Pred Value 0.78947 0.6301 0.8103 0.8872
## Neg Pred Value 0.98758 0.9851 0.8400 0.8846
## Prevalence 0.05572 0.1466 0.3812 0.4164
## Detection Rate 0.04399 0.1349 0.2757 0.3460
## Detection Prevalence 0.05572 0.2141 0.3402 0.3900
## Balanced Accuracy 0.88853 0.9136 0.8094 0.8778
## [1] "VARIABLES:A7,A64,A25,A3,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.68642 -0.20705 0.03576 0.22191 0.58950
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.6741 1.3147 68.211 1.12e-14 ***
## A7 29.7578 6.1643 4.827 0.000694 ***
## A64 -0.3628 0.1662 -2.183 0.053979 .
## A25 -1.4134 0.3440 -4.109 0.002115 **
## A3 -2.6879 2.2777 -1.180 0.265287
## A9 0.1463 2.4870 0.059 0.954249
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3955 on 10 degrees of freedom
## Multiple R-squared: 0.8784, Adjusted R-squared: 0.8176
## F-statistic: 14.45 on 5 and 10 DF, p-value: 0.0002657
##
## A7 A64 A25 A3 A9
## 1.548351 1.424205 1.301316 1.539457 1.261048
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 82"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 5 0 0
## Medio 3 43 12 2
## Alto 0 0 106 22
## Excelente 0 0 14 108
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.3871
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7512
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.89655 0.8958 0.8030 0.8182
## Specificity 0.98397 0.9420 0.8947 0.9330
## Pos Pred Value 0.83871 0.7167 0.8281 0.8852
## Neg Pred Value 0.99032 0.9822 0.8779 0.8904
## Prevalence 0.08504 0.1408 0.3871 0.3871
## Detection Rate 0.07625 0.1261 0.3109 0.3167
## Detection Prevalence 0.09091 0.1760 0.3754 0.3578
## Balanced Accuracy 0.94026 0.9189 0.8489 0.8756
## [1] "VARIABLES:A7,A64,A25,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64213 -0.16992 -0.04091 0.27628 0.50961
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.9156 1.2676 70.146 6.14e-16 ***
## A7 26.6358 5.0065 5.320 0.000245 ***
## A64 -0.4558 0.1411 -3.230 0.008008 **
## A25 -1.3973 0.2966 -4.711 0.000639 ***
## A77 1.1995 0.8169 1.468 0.169991
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3682 on 11 degrees of freedom
## Multiple R-squared: 0.8841, Adjusted R-squared: 0.8419
## F-statistic: 20.98 on 4 and 11 DF, p-value: 4.175e-05
##
## A7 A64 A25 A77
## 1.178689 1.184632 1.116400 1.053620
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 83"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 2 0 0
## Medio 10 40 14 0
## Alto 0 0 91 21
## Excelente 0 0 12 124
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7476
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.72973 0.9524 0.7778 0.8552
## Specificity 0.99342 0.9197 0.9062 0.9388
## Pos Pred Value 0.93103 0.6250 0.8125 0.9118
## Neg Pred Value 0.96795 0.9928 0.8865 0.8976
## Prevalence 0.10850 0.1232 0.3431 0.4252
## Detection Rate 0.07918 0.1173 0.2669 0.3636
## Detection Prevalence 0.08504 0.1877 0.3284 0.3988
## Balanced Accuracy 0.86158 0.9361 0.8420 0.8970
## [1] "VARIABLES:A7,A64,A60,A82"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.62316 -0.44615 0.08399 0.28545 0.70208
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.6077 0.9761 86.679 < 2e-16 ***
## A7 27.4360 7.2059 3.807 0.00291 **
## A64 -0.5316 0.2219 -2.395 0.03553 *
## A60 1.2913 0.9438 1.368 0.19857
## A82 0.2294 0.1056 2.172 0.05258 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5273 on 11 degrees of freedom
## Multiple R-squared: 0.7623, Adjusted R-squared: 0.6759
## F-statistic: 8.819 on 4 and 11 DF, p-value: 0.001921
##
## A7 A64 A60 A82
## 1.190629 1.429028 1.112896 1.316347
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 84"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 4 0 0
## Medio 4 25 5 0
## Alto 0 16 114 25
## Excelente 0 0 16 111
##
## Overall Statistics
##
## Accuracy : 0.7947
## 95% CI : (0.7479, 0.8363)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6856
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.84000 0.55556 0.8444 0.8162
## Specificity 0.98734 0.96959 0.8010 0.9220
## Pos Pred Value 0.84000 0.73529 0.7355 0.8740
## Neg Pred Value 0.98734 0.93485 0.8871 0.8832
## Prevalence 0.07331 0.13196 0.3959 0.3988
## Detection Rate 0.06158 0.07331 0.3343 0.3255
## Detection Prevalence 0.07331 0.09971 0.4545 0.3724
## Balanced Accuracy 0.91367 0.76258 0.8227 0.8691
## [1] "VARIABLES:A7,A7,A53,A10"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.71381 -0.22979 0.04835 0.23414 0.48454
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.1663 0.7469 115.366 < 2e-16 ***
## A7 20.5925 6.0546 3.401 0.005259 **
## A53 -5.8232 1.3205 -4.410 0.000851 ***
## A10 2.5682 1.2339 2.081 0.059474 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.392 on 12 degrees of freedom
## Multiple R-squared: 0.8567, Adjusted R-squared: 0.8209
## F-statistic: 23.91 on 3 and 12 DF, p-value: 2.379e-05
##
## A7 A53 A10
## 1.520944 1.171661 1.327926
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 85"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 0
## Medio 5 39 13 2
## Alto 0 0 114 22
## Excelente 0 0 16 108
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7315
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.79167 0.9286 0.7972 0.8182
## Specificity 0.99054 0.9331 0.8889 0.9234
## Pos Pred Value 0.86364 0.6610 0.8382 0.8710
## Neg Pred Value 0.98433 0.9894 0.8585 0.8894
## Prevalence 0.07038 0.1232 0.4194 0.3871
## Detection Rate 0.05572 0.1144 0.3343 0.3167
## Detection Prevalence 0.06452 0.1730 0.3988 0.3636
## Balanced Accuracy 0.89110 0.9308 0.8430 0.8708
## [1] "VARIABLES:A7,A64,A30,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.4094 -0.1874 0.0264 0.2311 0.3641
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 90.4038 1.0423 86.733 < 2e-16 ***
## A7 18.2410 4.6103 3.957 0.002247 **
## A64 -0.3145 0.1172 -2.684 0.021248 *
## A30 -1.7321 0.2931 -5.910 0.000102 ***
## A9 -4.6388 1.7907 -2.591 0.025114 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3027 on 11 degrees of freedom
## Multiple R-squared: 0.9216, Adjusted R-squared: 0.8931
## F-statistic: 32.34 on 4 and 11 DF, p-value: 5.02e-06
##
## A7 A64 A30 A9
## 1.478375 1.208231 1.429581 1.115961
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 86"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 4 0 0
## Medio 3 44 11 1
## Alto 0 0 107 15
## Excelente 0 0 15 114
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.39
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7899
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90000 0.9167 0.8045 0.8769
## Specificity 0.98714 0.9488 0.9279 0.9289
## Pos Pred Value 0.87097 0.7458 0.8770 0.8837
## Neg Pred Value 0.99032 0.9858 0.8813 0.9245
## Prevalence 0.08798 0.1408 0.3900 0.3812
## Detection Rate 0.07918 0.1290 0.3138 0.3343
## Detection Prevalence 0.09091 0.1730 0.3578 0.3783
## Balanced Accuracy 0.94357 0.9327 0.8662 0.9029
## [1] "VARIABLES:A7,A64,A82,A41"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8265 -0.3725 0.1163 0.3125 0.7653
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.5605 1.2737 66.387 1.12e-15 ***
## A7 29.4146 7.5149 3.914 0.00242 **
## A64 -0.3923 0.2675 -1.466 0.17058
## A82 0.2057 0.1119 1.838 0.09321 .
## A41 1.0421 1.9103 0.546 0.59628
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5628 on 11 degrees of freedom
## Multiple R-squared: 0.7292, Adjusted R-squared: 0.6307
## F-statistic: 7.404 on 4 and 11 DF, p-value: 0.003799
##
## A7 A64 A82 A41
## 1.136552 1.822422 1.297544 1.702802
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 87"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 16 2 0 1
## Medio 3 46 12 0
## Alto 0 0 107 23
## Excelente 0 0 17 114
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7439
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.84211 0.9583 0.7868 0.8261
## Specificity 0.99068 0.9488 0.8878 0.9163
## Pos Pred Value 0.84211 0.7541 0.8231 0.8702
## Neg Pred Value 0.99068 0.9929 0.8626 0.8857
## Prevalence 0.05572 0.1408 0.3988 0.4047
## Detection Rate 0.04692 0.1349 0.3138 0.3343
## Detection Prevalence 0.05572 0.1789 0.3812 0.3842
## Balanced Accuracy 0.91639 0.9536 0.8373 0.8712
## [1] "VARIABLES:A7,A64,A80,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.63853 -0.25997 0.01322 0.29230 0.89139
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 81.1259 1.6470 49.256 2.96e-14 ***
## A7 34.6720 6.5782 5.271 0.000264 ***
## A64 -0.2554 0.1828 -1.397 0.189948
## A80 1.9921 0.7136 2.792 0.017538 *
## A77 3.9567 1.6279 2.430 0.033381 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4893 on 11 degrees of freedom
## Multiple R-squared: 0.7953, Adjusted R-squared: 0.7208
## F-statistic: 10.68 on 4 and 11 DF, p-value: 0.0008741
##
## A7 A64 A80 A77
## 1.152135 1.125725 2.346620 2.369173
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 88"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 4 0 0
## Medio 6 34 12 0
## Alto 0 0 98 24
## Excelente 0 0 22 121
##
## Overall Statistics
##
## Accuracy : 0.8006
## 95% CI : (0.7542, 0.8417)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6982
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76923 0.89474 0.7424 0.8345
## Specificity 0.98730 0.94059 0.8852 0.8878
## Pos Pred Value 0.83333 0.65385 0.8033 0.8462
## Neg Pred Value 0.98107 0.98616 0.8447 0.8788
## Prevalence 0.07625 0.11144 0.3871 0.4252
## Detection Rate 0.05865 0.09971 0.2874 0.3548
## Detection Prevalence 0.07038 0.15249 0.3578 0.4194
## Balanced Accuracy 0.87827 0.91767 0.8138 0.8611
## [1] "VARIABLES:A7,A64,A60,A26"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.57263 -0.33973 0.03438 0.32933 0.60020
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 90.5045 1.9739 45.850 6.5e-14 ***
## A7 20.6546 6.6880 3.088 0.01032 *
## A64 -0.1489 0.1740 -0.856 0.41025
## A60 -0.7170 0.8906 -0.805 0.43784
## A26 -3.2293 0.9794 -3.297 0.00711 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.447 on 11 degrees of freedom
## Multiple R-squared: 0.8292, Adjusted R-squared: 0.7671
## F-statistic: 13.35 on 4 and 11 DF, p-value: 0.0003343
##
## A7 A64 A60 A26
## 1.427224 1.222121 1.378859 1.894099
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 89"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 2 0 1
## Medio 7 45 12 0
## Alto 0 0 111 21
## Excelente 0 0 15 104
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7505
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76667 0.9574 0.8043 0.8254
## Specificity 0.99035 0.9354 0.8966 0.9302
## Pos Pred Value 0.88462 0.7031 0.8409 0.8739
## Neg Pred Value 0.97778 0.9928 0.8708 0.9009
## Prevalence 0.08798 0.1378 0.4047 0.3695
## Detection Rate 0.06745 0.1320 0.3255 0.3050
## Detection Prevalence 0.07625 0.1877 0.3871 0.3490
## Balanced Accuracy 0.87851 0.9464 0.8504 0.8778
## [1] "VARIABLES:A7,A64,A41,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97124 -0.41033 0.08358 0.42657 0.72967
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.1067 1.4352 59.300 3.88e-15 ***
## A7 31.7803 8.1439 3.902 0.00247 **
## A64 -0.3066 0.2861 -1.072 0.30686
## A41 0.6288 2.0742 0.303 0.76744
## A9 -3.7005 3.6983 -1.001 0.33852
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.616 on 11 degrees of freedom
## Multiple R-squared: 0.6755, Adjusted R-squared: 0.5576
## F-statistic: 5.726 on 4 and 11 DF, p-value: 0.009658
##
## A7 A64 A41 A9
## 1.114140 1.739638 1.675546 1.149645
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 90"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 4 0 0
## Medio 5 40 5 1
## Alto 0 0 117 16
## Excelente 0 0 19 109
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7822
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.83333 0.9091 0.8298 0.8651
## Specificity 0.98714 0.9630 0.9200 0.9116
## Pos Pred Value 0.86207 0.7843 0.8797 0.8516
## Neg Pred Value 0.98397 0.9862 0.8846 0.9202
## Prevalence 0.08798 0.1290 0.4135 0.3695
## Detection Rate 0.07331 0.1173 0.3431 0.3196
## Detection Prevalence 0.08504 0.1496 0.3900 0.3754
## Balanced Accuracy 0.91024 0.9360 0.8749 0.8884
## [1] "VARIABLES:A7,A64,A25,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64213 -0.16992 -0.04091 0.27628 0.50961
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.9156 1.2676 70.146 6.14e-16 ***
## A7 26.6358 5.0065 5.320 0.000245 ***
## A64 -0.4558 0.1411 -3.230 0.008008 **
## A25 -1.3973 0.2966 -4.711 0.000639 ***
## A77 1.1995 0.8169 1.468 0.169991
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3682 on 11 degrees of freedom
## Multiple R-squared: 0.8841, Adjusted R-squared: 0.8419
## F-statistic: 20.98 on 4 and 11 DF, p-value: 4.175e-05
##
## A7 A64 A25 A77
## 1.178689 1.184632 1.116400 1.053620
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 91"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 1 0 0
## Medio 4 35 10 0
## Alto 0 11 126 29
## Excelente 0 0 7 92
##
## Overall Statistics
##
## Accuracy : 0.8182
## 95% CI : (0.7731, 0.8577)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.727
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.86667 0.7447 0.8811 0.7603
## Specificity 0.99678 0.9524 0.7980 0.9682
## Pos Pred Value 0.96296 0.7143 0.7590 0.9293
## Neg Pred Value 0.98726 0.9589 0.9029 0.8802
## Prevalence 0.08798 0.1378 0.4194 0.3548
## Detection Rate 0.07625 0.1026 0.3695 0.2698
## Detection Prevalence 0.07918 0.1437 0.4868 0.2903
## Balanced Accuracy 0.93173 0.8485 0.8395 0.8643
## [1] "VARIABLES:A7,A7,A60,A10"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.14059 -0.28149 -0.04218 0.42017 0.88281
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.186 1.069 78.774 < 2e-16 ***
## A7 29.142 9.097 3.203 0.00758 **
## A60 0.822 1.085 0.758 0.46336
## A10 2.124 1.972 1.077 0.30281
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6199 on 12 degrees of freedom
## Multiple R-squared: 0.6416, Adjusted R-squared: 0.552
## F-statistic: 7.16 on 3 and 12 DF, p-value: 0.005173
##
## A7 A60 A10
## 1.372872 1.064326 1.356933
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 92"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 0 1 0
## Medio 12 42 11 0
## Alto 0 0 103 21
## Excelente 0 0 15 114
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7418
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.64706 1.0000 0.7923 0.8444
## Specificity 0.99674 0.9231 0.9005 0.9272
## Pos Pred Value 0.95652 0.6462 0.8306 0.8837
## Neg Pred Value 0.96226 1.0000 0.8756 0.9009
## Prevalence 0.09971 0.1232 0.3812 0.3959
## Detection Rate 0.06452 0.1232 0.3021 0.3343
## Detection Prevalence 0.06745 0.1906 0.3636 0.3783
## Balanced Accuracy 0.82190 0.9615 0.8464 0.8858
## [1] "VARIABLES:A7,A64,A64,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 93"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 0 0 0
## Medio 8 47 14 2
## Alto 0 0 107 20
## Excelente 0 0 9 112
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7728
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 1.0000 0.8231 0.8358
## Specificity 1.00000 0.9184 0.9052 0.9565
## Pos Pred Value 1.00000 0.6620 0.8425 0.9256
## Neg Pred Value 0.97492 1.0000 0.8925 0.9000
## Prevalence 0.08798 0.1378 0.3812 0.3930
## Detection Rate 0.06452 0.1378 0.3138 0.3284
## Detection Prevalence 0.06452 0.2082 0.3724 0.3548
## Balanced Accuracy 0.86667 0.9592 0.8641 0.8962
## [1] "VARIABLES:A7,A64,A64,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 94"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 0 0 0
## Medio 8 39 16 0
## Alto 0 0 111 24
## Excelente 0 0 15 101
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7288
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.77143 1.0000 0.7817 0.8080
## Specificity 1.00000 0.9205 0.8794 0.9306
## Pos Pred Value 1.00000 0.6190 0.8222 0.8707
## Neg Pred Value 0.97452 1.0000 0.8495 0.8933
## Prevalence 0.10264 0.1144 0.4164 0.3666
## Detection Rate 0.07918 0.1144 0.3255 0.2962
## Detection Prevalence 0.07918 0.1848 0.3959 0.3402
## Balanced Accuracy 0.88571 0.9603 0.8305 0.8693
## [1] "VARIABLES:A7,A64,A6,A3,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.90099 -0.22575 -0.04526 0.29340 0.71132
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.6829 1.0685 80.191 2.22e-15 ***
## A7 34.0781 8.3389 4.087 0.00219 **
## A64 -0.5151 0.2381 -2.163 0.05580 .
## A6 -0.5511 0.2544 -2.166 0.05552 .
## A3 2.5763 3.2731 0.787 0.44948
## A9 -5.0977 3.2370 -1.575 0.14638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.535 on 10 degrees of freedom
## Multiple R-squared: 0.7775, Adjusted R-squared: 0.6663
## F-statistic: 6.99 on 5 and 10 DF, p-value: 0.004703
##
## A7 A64 A6 A3 A9
## 1.548757 1.598013 1.475520 1.737614 1.167730
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 95"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 1 0 0
## Medio 10 52 13 0
## Alto 0 0 106 14
## Excelente 0 0 17 107
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7664
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.67742 0.9811 0.7794 0.8843
## Specificity 0.99677 0.9201 0.9317 0.9227
## Pos Pred Value 0.95455 0.6933 0.8833 0.8629
## Neg Pred Value 0.96865 0.9962 0.8643 0.9355
## Prevalence 0.09091 0.1554 0.3988 0.3548
## Detection Rate 0.06158 0.1525 0.3109 0.3138
## Detection Prevalence 0.06452 0.2199 0.3519 0.3636
## Balanced Accuracy 0.83710 0.9506 0.8556 0.9035
## [1] "VARIABLES:A7,A64,A35,A12,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.4910 -0.2952 -0.1835 0.3650 0.7123
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.8763 0.9896 86.777 1.01e-15 ***
## A7 25.9020 7.5892 3.413 0.00663 **
## A64 -0.2888 0.2004 -1.441 0.18013
## A35 -24.2435 9.0262 -2.686 0.02286 *
## A12 1.0805 2.3322 0.463 0.65307
## A9 1.5743 3.8171 0.412 0.68871
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4928 on 10 degrees of freedom
## Multiple R-squared: 0.8112, Adjusted R-squared: 0.7168
## F-statistic: 8.594 on 5 and 10 DF, p-value: 0.002177
##
## A7 A64 A35 A12 A9
## 1.511716 1.333397 1.475374 1.683865 1.913452
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 96"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 3 0 0
## Medio 0 40 16 1
## Alto 0 2 106 27
## Excelente 0 0 12 113
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7316
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 1.00000 0.8889 0.7910 0.8014
## Specificity 0.99062 0.9426 0.8599 0.9400
## Pos Pred Value 0.87500 0.7018 0.7852 0.9040
## Neg Pred Value 1.00000 0.9824 0.8641 0.8704
## Prevalence 0.06158 0.1320 0.3930 0.4135
## Detection Rate 0.06158 0.1173 0.3109 0.3314
## Detection Prevalence 0.07038 0.1672 0.3959 0.3666
## Balanced Accuracy 0.99531 0.9157 0.8255 0.8707
## [1] "VARIABLES:A7,A64,A36,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81566 -0.38455 -0.02778 0.49495 0.60408
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.4675 1.5903 54.372 1e-14 ***
## A7 25.6422 9.8006 2.616 0.024 *
## A64 -0.2477 0.2506 -0.988 0.344
## A36 -1.0266 0.9932 -1.034 0.324
## A9 -2.6147 3.5699 -0.732 0.479
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5906 on 11 degrees of freedom
## Multiple R-squared: 0.7018, Adjusted R-squared: 0.5934
## F-statistic: 6.472 on 4 and 11 DF, p-value: 0.006258
##
## A7 A64 A36 A9
## 1.755579 1.452064 2.076374 1.165528
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 97"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 3 0 0
## Medio 9 26 7 0
## Alto 0 11 108 35
## Excelente 0 0 13 107
##
## Overall Statistics
##
## Accuracy : 0.7713
## 95% CI : (0.723, 0.8148)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6549
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.70968 0.65000 0.8438 0.7535
## Specificity 0.99032 0.94684 0.7840 0.9347
## Pos Pred Value 0.88000 0.61905 0.7013 0.8917
## Neg Pred Value 0.97152 0.95318 0.8930 0.8416
## Prevalence 0.09091 0.11730 0.3754 0.4164
## Detection Rate 0.06452 0.07625 0.3167 0.3138
## Detection Prevalence 0.07331 0.12317 0.4516 0.3519
## Balanced Accuracy 0.85000 0.79842 0.8139 0.8441
## [1] "VARIABLES:A7,A7,A53,A3"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.75280 -0.17203 0.02708 0.16914 0.71797
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.9326 0.7974 107.762 < 2e-16 ***
## A7 21.2971 7.1241 2.989 0.01129 *
## A53 -6.6155 1.6826 -3.932 0.00199 **
## A3 3.3774 2.5779 1.310 0.21467
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4277 on 12 degrees of freedom
## Multiple R-squared: 0.8294, Adjusted R-squared: 0.7867
## F-statistic: 19.44 on 3 and 12 DF, p-value: 6.69e-05
##
## A7 A53 A3
## 1.768434 1.597601 1.686268
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 98"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 3
## Medio 5 45 14 0
## Alto 0 0 114 14
## Excelente 0 0 11 113
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7833
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.79167 0.9375 0.8201 0.8692
## Specificity 0.98107 0.9352 0.9307 0.9479
## Pos Pred Value 0.76000 0.7031 0.8906 0.9113
## Neg Pred Value 0.98418 0.9892 0.8826 0.9217
## Prevalence 0.07038 0.1408 0.4076 0.3812
## Detection Rate 0.05572 0.1320 0.3343 0.3314
## Detection Prevalence 0.07331 0.1877 0.3754 0.3636
## Balanced Accuracy 0.88637 0.9363 0.8754 0.9085
## [1] "VARIABLES:A7,A64,A64,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9826 -0.3928 0.1304 0.4356 0.6916
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.3414 1.1617 73.460 < 2e-16 ***
## A7 31.7656 7.8295 4.057 0.00159 **
## A64 -0.3547 0.2288 -1.550 0.14712
## A9 -3.4733 3.4818 -0.998 0.33819
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5923 on 12 degrees of freedom
## Multiple R-squared: 0.6728, Adjusted R-squared: 0.591
## F-statistic: 8.226 on 3 and 12 DF, p-value: 0.00305
##
## A7 A64 A9
## 1.114100 1.204165 1.102425
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 99"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 4 0 0
## Medio 3 49 15 4
## Alto 0 0 116 21
## Excelente 0 0 12 92
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7483
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.89286 0.9245 0.8112 0.7863
## Specificity 0.98722 0.9236 0.8939 0.9464
## Pos Pred Value 0.86207 0.6901 0.8467 0.8846
## Neg Pred Value 0.99038 0.9852 0.8676 0.8945
## Prevalence 0.08211 0.1554 0.4194 0.3431
## Detection Rate 0.07331 0.1437 0.3402 0.2698
## Detection Prevalence 0.08504 0.2082 0.4018 0.3050
## Balanced Accuracy 0.94004 0.9241 0.8526 0.8664
## [1] "VARIABLES:A7,A64,A36,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81566 -0.38455 -0.02778 0.49495 0.60408
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.4675 1.5903 54.372 1e-14 ***
## A7 25.6422 9.8006 2.616 0.024 *
## A64 -0.2477 0.2506 -0.988 0.344
## A36 -1.0266 0.9932 -1.034 0.324
## A9 -2.6147 3.5699 -0.732 0.479
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5906 on 11 degrees of freedom
## Multiple R-squared: 0.7018, Adjusted R-squared: 0.5934
## F-statistic: 6.472 on 4 and 11 DF, p-value: 0.006258
##
## A7 A64 A36 A9
## 1.755579 1.452064 2.076374 1.165528
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 100"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 0 0 0
## Medio 5 41 12 0
## Alto 0 0 97 23
## Excelente 0 0 17 128
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4428
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7458
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78261 1.0000 0.7698 0.8477
## Specificity 1.00000 0.9433 0.8930 0.9105
## Pos Pred Value 1.00000 0.7069 0.8083 0.8828
## Neg Pred Value 0.98452 1.0000 0.8688 0.8827
## Prevalence 0.06745 0.1202 0.3695 0.4428
## Detection Rate 0.05279 0.1202 0.2845 0.3754
## Detection Prevalence 0.05279 0.1701 0.3519 0.4252
## Balanced Accuracy 0.89130 0.9717 0.8314 0.8791
## [1] "VARIABLES:A7,A64,A64,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.13108 -0.43106 0.04603 0.38812 0.78935
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4781 1.4106 59.886 3.11e-16 ***
## A7 31.7573 8.1277 3.907 0.00208 **
## A64 -0.2980 0.2280 -1.307 0.21559
## A77 0.5294 1.3378 0.396 0.69926
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6123 on 12 degrees of freedom
## Multiple R-squared: 0.6503, Adjusted R-squared: 0.5628
## F-statistic: 7.437 on 3 and 12 DF, p-value: 0.004489
##
## A7 A64 A77
## 1.123108 1.117863 1.021665
## [1] "--------------------------------------------------------------------------------------"print(vv)## [1] 0 0 8 0 0 11 116 0 37 6 0 3 0 0 0 0 0 0 0
## [20] 0 0 0 0 3 13 1 0 2 1 1 0 0 2 0 2 15 12 10
## [39] 0 1 12 0 0 2 0 0 0 0 0 0 0 0 5 0 0 2 1
## [58] 0 0 6 0 2 0 105 0 0 0 0 0 0 0 0 0 0 0 3
## [77] 16 1 0 3 0 9 2 1 0 0print(paste0("Mejor conjunto de Variables",vx2))## [1] "Mejor conjunto de VariablesA7+A64+A6+A24"Compuestos seleccionados
mm0<-import("PolarCorrelation.xlsx")
mm0<-mm0 %>% mutate(Total=Aroma+Flavor+Aftertaste+Acidity+Body+Balance+Overall+30)
nombres=names(mm0[,1:86])
codigo=c(gsub(" ","",paste("A",1:86)))
names(mm0)<-c(gsub(" ","",paste("A",1:86)),"Aroma","Flavor","Aftertaste","Acidity","Body","Balance","Overall","Total")
compuestos<-data.frame(codigo=codigo,nombre=nombres,nv=vv)
#compuestos
n=vv>8
dfCompuestos<-compuestos[n,]
dfCompuestos## codigo nombre nv
## 6 A6 Ethanol 11
## 7 A7 2,3-Butanedione 116
## 9 A9 2,3-Pentanedione 37
## 25 A25 Pyrazine, 2,6-dimethyl- 13
## 36 A36 2,6-Diethylpyrazine 15
## 37 A37 Pyrazine, 2-methyl-6-propyl- 12
## 38 A38 Furfural 10
## 41 A41 2,5-dimethyl-3(2H)-furanone 12
## 64 A64 1H-Pyrrole, 1-(2-furanylmethyl)- 105
## 77 A77 1H-Pyrrole-2-carboxaldehyde, 1-methyl- 16
## 82 A82 Caffeine 9new_string <- paste(dfCompuestos$codigo, collapse = "+")Predicción de datos originales columna Polar
modelo1<-lm(Total~A7+A64+A6+A24,data=mm0)
#modelo1<-lm(Total~A7+A64+A30+A9,data=mm0)
#modelo1<-lm(Total~A7+A64+A6+A25,data=mm0)
summary(modelo1)##
## Call:
## lm(formula = Total ~ A7 + A64 + A6 + A24, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.37508 -0.18545 -0.07095 0.11648 0.54901
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.6283 1.0382 86.330 < 2e-16 ***
## A7 26.8059 4.5543 5.886 0.000105 ***
## A64 -0.4597 0.1159 -3.966 0.002210 **
## A6 -0.4303 0.1290 -3.336 0.006639 **
## A24 -1.1095 0.2065 -5.372 0.000226 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3035 on 11 degrees of freedom
## Multiple R-squared: 0.9213, Adjusted R-squared: 0.8926
## F-statistic: 32.18 on 4 and 11 DF, p-value: 5.152e-06vif(modelo1)## A7 A64 A6 A24
## 1.435801 1.176464 1.178775 1.191733plot(modelo1$fitted.values,mm0$Total)
abline(0,1,col="orange")
intervalos_confianza <- confint(modelo1)
# Mostrar los intervalos de confianza de los coeficientes de regresión
print(intervalos_confianza)## 2.5 % 97.5 %
## (Intercept) 87.3432157 91.9133551
## A7 16.7819371 36.8299532
## A64 -0.7147766 -0.2045967
## A6 -0.7141968 -0.1464142
## A24 -1.5639854 -0.6549203