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 13 0 0 0
## Medio 9 36 14 1
## Alto 0 0 124 19
## Excelente 0 0 14 111
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4457
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7433
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.59091 1.0000 0.8158 0.8473
## Specificity 1.00000 0.9213 0.8995 0.9333
## Pos Pred Value 1.00000 0.6000 0.8671 0.8880
## Neg Pred Value 0.97256 1.0000 0.8586 0.9074
## Prevalence 0.06452 0.1056 0.4457 0.3842
## Detection Rate 0.03812 0.1056 0.3636 0.3255
## Detection Prevalence 0.03812 0.1760 0.4194 0.3666
## Balanced Accuracy 0.79545 0.9607 0.8576 0.8903
## [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 2"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 5 0 0
## Medio 3 36 18 0
## Alto 0 0 115 19
## Excelente 0 0 15 110
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.434
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7357
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.86957 0.8780 0.7770 0.8527
## Specificity 0.98428 0.9300 0.9016 0.9292
## Pos Pred Value 0.80000 0.6316 0.8582 0.8800
## Neg Pred Value 0.99051 0.9824 0.8406 0.9120
## Prevalence 0.06745 0.1202 0.4340 0.3783
## Detection Rate 0.05865 0.1056 0.3372 0.3226
## Detection Prevalence 0.07331 0.1672 0.3930 0.3666
## Balanced Accuracy 0.92692 0.9040 0.8393 0.8910
## [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 3"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 1 0 0
## Medio 8 44 14 7
## Alto 0 0 120 23
## Excelente 0 0 3 101
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7589
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 0.9778 0.8759 0.7710
## Specificity 0.99681 0.9020 0.8873 0.9857
## Pos Pred Value 0.95238 0.6027 0.8392 0.9712
## Neg Pred Value 0.97500 0.9963 0.9141 0.8734
## Prevalence 0.08211 0.1320 0.4018 0.3842
## Detection Rate 0.05865 0.1290 0.3519 0.2962
## Detection Prevalence 0.06158 0.2141 0.4194 0.3050
## Balanced Accuracy 0.85555 0.9399 0.8816 0.8784
## [1] "VARIABLES:A7,A64,A53,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84087 -0.22498 -0.05176 0.25096 0.66233
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.477254 1.004437 85.100 < 2e-16 ***
## A7 27.083754 6.449408 4.199 0.00149 **
## A64 -0.002974 0.200411 -0.015 0.98843
## A53 -5.441273 1.800090 -3.023 0.01160 *
## A38 0.028845 0.059628 0.484 0.63805
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4726 on 11 degrees of freedom
## Multiple R-squared: 0.809, Adjusted R-squared: 0.7396
## F-statistic: 11.65 on 4 and 11 DF, p-value: 0.0006052
##
## A7 A64 A53 A38
## 1.187041 1.450266 1.497607 1.011657
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 4"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 2 0 0
## Medio 5 45 13 2
## Alto 0 0 130 26
## Excelente 0 0 4 90
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4311
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.774
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82759 0.9574 0.8844 0.7627
## Specificity 0.99359 0.9320 0.8660 0.9821
## Pos Pred Value 0.92308 0.6923 0.8333 0.9574
## Neg Pred Value 0.98413 0.9928 0.9081 0.8866
## Prevalence 0.08504 0.1378 0.4311 0.3460
## Detection Rate 0.07038 0.1320 0.3812 0.2639
## Detection Prevalence 0.07625 0.1906 0.4575 0.2757
## Balanced Accuracy 0.91059 0.9447 0.8752 0.8724
## [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 5"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 10 3 0 1
## Medio 5 37 12 1
## Alto 0 0 133 27
## Excelente 0 0 7 105
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4457
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7438
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.66667 0.9250 0.8750 0.7836
## Specificity 0.98773 0.9402 0.8571 0.9662
## Pos Pred Value 0.71429 0.6727 0.8312 0.9375
## Neg Pred Value 0.98471 0.9895 0.8950 0.8734
## Prevalence 0.04399 0.1173 0.4457 0.3930
## Detection Rate 0.02933 0.1085 0.3900 0.3079
## Detection Prevalence 0.04106 0.1613 0.4692 0.3284
## Balanced Accuracy 0.82720 0.9326 0.8661 0.8749
## [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 6"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 0
## Medio 11 45 8 3
## Alto 0 0 104 20
## Excelente 0 0 19 107
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.3842
## 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 0.66667 0.9574 0.7939 0.8231
## Specificity 0.99351 0.9252 0.9048 0.9100
## Pos Pred Value 0.91667 0.6716 0.8387 0.8492
## Neg Pred Value 0.96530 0.9927 0.8756 0.8930
## Prevalence 0.09677 0.1378 0.3842 0.3812
## Detection Rate 0.06452 0.1320 0.3050 0.3138
## Detection Prevalence 0.07038 0.1965 0.3636 0.3695
## Balanced Accuracy 0.83009 0.9413 0.8493 0.8665
## [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 7"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 2 0 0
## Medio 8 40 5 1
## Alto 0 11 112 24
## Excelente 0 0 12 109
##
## Overall Statistics
##
## Accuracy : 0.8152
## 95% CI : (0.7699, 0.855)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7238
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.68000 0.7547 0.8682 0.8134
## Specificity 0.99367 0.9514 0.8349 0.9420
## Pos Pred Value 0.89474 0.7407 0.7619 0.9008
## Neg Pred Value 0.97516 0.9547 0.9124 0.8864
## Prevalence 0.07331 0.1554 0.3783 0.3930
## Detection Rate 0.04985 0.1173 0.3284 0.3196
## Detection Prevalence 0.05572 0.1584 0.4311 0.3548
## Balanced Accuracy 0.83684 0.8531 0.8516 0.8777
## [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 8"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 2 0 1
## Medio 7 41 10 2
## Alto 0 0 112 17
## Excelente 0 0 14 118
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4047
## 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 0.70833 0.9535 0.8235 0.8551
## Specificity 0.99054 0.9362 0.9171 0.9310
## Pos Pred Value 0.85000 0.6833 0.8682 0.8939
## Neg Pred Value 0.97819 0.9929 0.8868 0.9043
## Prevalence 0.07038 0.1261 0.3988 0.4047
## Detection Rate 0.04985 0.1202 0.3284 0.3460
## Detection Prevalence 0.05865 0.1760 0.3783 0.3871
## Balanced Accuracy 0.84943 0.9449 0.8703 0.8931
## [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 9"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 15 0 0 0
## Medio 12 39 14 1
## Alto 0 0 119 37
## Excelente 0 0 5 99
##
## Overall Statistics
##
## Accuracy : 0.7977
## 95% CI : (0.751, 0.839)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6965
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.55556 1.0000 0.8623 0.7226
## Specificity 1.00000 0.9106 0.8177 0.9755
## Pos Pred Value 1.00000 0.5909 0.7628 0.9519
## Neg Pred Value 0.96319 1.0000 0.8973 0.8397
## Prevalence 0.07918 0.1144 0.4047 0.4018
## Detection Rate 0.04399 0.1144 0.3490 0.2903
## Detection Prevalence 0.04399 0.1935 0.4575 0.3050
## Balanced Accuracy 0.77778 0.9553 0.8400 0.8491
## [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 10"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 4 52 14 0
## Alto 0 0 109 17
## Excelente 0 0 12 111
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7891
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.83333 0.9630 0.8074 0.8672
## Specificity 0.99369 0.9373 0.9175 0.9437
## Pos Pred Value 0.90909 0.7429 0.8651 0.9024
## Neg Pred Value 0.98746 0.9926 0.8791 0.9220
## Prevalence 0.07038 0.1584 0.3959 0.3754
## Detection Rate 0.05865 0.1525 0.3196 0.3255
## Detection Prevalence 0.06452 0.2053 0.3695 0.3607
## Balanced Accuracy 0.91351 0.9501 0.8624 0.9054
## [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 11"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 2 0 0
## Medio 9 35 12 2
## Alto 0 0 113 20
## Excelente 0 0 13 112
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7472
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71875 0.9459 0.8188 0.8358
## Specificity 0.99353 0.9243 0.9015 0.9372
## Pos Pred Value 0.92000 0.6034 0.8496 0.8960
## Neg Pred Value 0.97152 0.9929 0.8798 0.8981
## Prevalence 0.09384 0.1085 0.4047 0.3930
## Detection Rate 0.06745 0.1026 0.3314 0.3284
## Detection Prevalence 0.07331 0.1701 0.3900 0.3666
## Balanced Accuracy 0.85614 0.9351 0.8602 0.8865
## [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 12"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 2 0 0
## Medio 6 44 13 1
## Alto 0 4 92 27
## Excelente 0 0 13 112
##
## Overall Statistics
##
## Accuracy : 0.8065
## 95% CI : (0.7605, 0.847)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7191
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.81818 0.8800 0.7797 0.8000
## Specificity 0.99351 0.9313 0.8610 0.9353
## Pos Pred Value 0.93103 0.6875 0.7480 0.8960
## Neg Pred Value 0.98077 0.9783 0.8807 0.8704
## Prevalence 0.09677 0.1466 0.3460 0.4106
## Detection Rate 0.07918 0.1290 0.2698 0.3284
## Detection Prevalence 0.08504 0.1877 0.3607 0.3666
## Balanced Accuracy 0.90584 0.9056 0.8203 0.8677
## [1] "VARIABLES:A7,A64,A36,A55,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.80727 -0.39439 -0.03309 0.49968 0.59500
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.4928 1.6806 51.465 1.86e-13 ***
## A7 25.0674 11.3763 2.203 0.0521 .
## A64 -0.2512 0.2644 -0.950 0.3644
## A36 -1.0304 1.0415 -0.989 0.3458
## A55 0.2319 1.9731 0.118 0.9088
## A9 -2.4217 4.0861 -0.593 0.5666
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.619 on 10 degrees of freedom
## Multiple R-squared: 0.7022, Adjusted R-squared: 0.5533
## F-statistic: 4.716 on 5 and 10 DF, p-value: 0.01793
##
## A7 A64 A36 A55 A9
## 2.153405 1.471546 2.078415 1.517545 1.390063
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 13"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 1 0 1
## Medio 7 38 14 0
## Alto 0 0 109 19
## Excelente 0 0 16 116
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7453
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.74074 0.9744 0.7842 0.8529
## Specificity 0.99363 0.9305 0.9059 0.9220
## Pos Pred Value 0.90909 0.6441 0.8516 0.8788
## Neg Pred Value 0.97806 0.9965 0.8592 0.9043
## Prevalence 0.07918 0.1144 0.4076 0.3988
## Detection Rate 0.05865 0.1114 0.3196 0.3402
## Detection Prevalence 0.06452 0.1730 0.3754 0.3871
## Balanced Accuracy 0.86719 0.9524 0.8451 0.8874
## [1] "VARIABLES:A7,A64,A60,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0055 -0.3068 -0.0774 0.3875 0.8471
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.9549 1.5579 53.890 1.11e-14 ***
## A7 30.6794 8.3282 3.684 0.0036 **
## A64 -0.3246 0.2330 -1.393 0.1910
## A60 0.9361 1.1135 0.841 0.4184
## A77 0.8565 1.4093 0.608 0.5557
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.62 on 11 degrees of freedom
## Multiple R-squared: 0.6714, Adjusted R-squared: 0.5519
## F-statistic: 5.618 on 4 and 11 DF, p-value: 0.01031
##
## A7 A64 A60 A77
## 1.150374 1.138854 1.120544 1.105997
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 14"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 3 0 0
## Medio 9 42 16 0
## Alto 0 3 119 22
## Excelente 0 1 6 97
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7426
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71875 0.8571 0.8440 0.8151
## Specificity 0.99029 0.9144 0.8750 0.9685
## Pos Pred Value 0.88462 0.6269 0.8264 0.9327
## Neg Pred Value 0.97143 0.9745 0.8883 0.9072
## Prevalence 0.09384 0.1437 0.4135 0.3490
## Detection Rate 0.06745 0.1232 0.3490 0.2845
## Detection Prevalence 0.07625 0.1965 0.4223 0.3050
## Balanced Accuracy 0.85452 0.8858 0.8595 0.8918
## [1] "VARIABLES:A7,A64,A84,A30"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7562 -0.2466 0.1068 0.2175 0.3911
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 90.3389 1.5770 57.284 5.67e-15 ***
## A7 15.1410 6.9331 2.184 0.05152 .
## A64 -0.1725 0.1569 -1.099 0.29508
## A84 -2.5322 3.0376 -0.834 0.42224
## A30 -1.5257 0.3876 -3.937 0.00233 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3726 on 11 degrees of freedom
## Multiple R-squared: 0.8813, Adjusted R-squared: 0.8382
## F-statistic: 20.42 on 4 and 11 DF, p-value: 4.741e-05
##
## A7 A64 A84 A30
## 2.207708 1.430032 3.155990 1.650607
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 15"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 1 0 0
## Medio 6 34 5 0
## Alto 0 9 117 20
## Excelente 0 0 16 112
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7465
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.77778 0.77273 0.8478 0.8485
## Specificity 0.99682 0.96296 0.8571 0.9234
## Pos Pred Value 0.95455 0.75556 0.8014 0.8750
## Neg Pred Value 0.98119 0.96622 0.8923 0.9061
## Prevalence 0.07918 0.12903 0.4047 0.3871
## Detection Rate 0.06158 0.09971 0.3431 0.3284
## Detection Prevalence 0.06452 0.13196 0.4282 0.3754
## Balanced Accuracy 0.88730 0.86785 0.8525 0.8860
## [1] "VARIABLES:A7,A7,A36,A10"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.86499 -0.32368 0.02305 0.32032 0.86078
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.6899 1.5355 56.458 6.29e-16 ***
## A7 19.3691 10.1777 1.903 0.0813 .
## A36 -1.5580 0.8589 -1.814 0.0948 .
## A10 2.0918 1.7591 1.189 0.2574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5622 on 12 degrees of freedom
## Multiple R-squared: 0.7052, Adjusted R-squared: 0.6316
## F-statistic: 9.571 on 3 and 12 DF, p-value: 0.001662
##
## A7 A36 A10
## 2.089629 1.713944 1.312327
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 16"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 0 0 0
## Medio 5 32 5 1
## Alto 0 14 110 35
## Excelente 0 0 8 110
##
## Overall Statistics
##
## Accuracy : 0.8006
## 95% CI : (0.7542, 0.8417)
## No Information Rate : 0.4282
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6987
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80769 0.69565 0.8943 0.7534
## Specificity 1.00000 0.96271 0.7752 0.9590
## Pos Pred Value 1.00000 0.74419 0.6918 0.9322
## Neg Pred Value 0.98438 0.95302 0.9286 0.8386
## Prevalence 0.07625 0.13490 0.3607 0.4282
## Detection Rate 0.06158 0.09384 0.3226 0.3226
## Detection Prevalence 0.06158 0.12610 0.4663 0.3460
## Balanced Accuracy 0.90385 0.82918 0.8348 0.8562
## [1] "VARIABLES:A7,A7,A64,A25"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74592 -0.18641 -0.00011 0.24310 0.61959
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.4624 1.2687 70.516 < 2e-16 ***
## A7 26.2162 5.2336 5.009 0.000305 ***
## A64 -0.4331 0.1469 -2.949 0.012161 *
## A25 -1.3214 0.3058 -4.321 0.000995 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3855 on 12 degrees of freedom
## Multiple R-squared: 0.8614, Adjusted R-squared: 0.8267
## F-statistic: 24.85 on 3 and 12 DF, p-value: 1.954e-05
##
## A7 A64 A25
## 1.174849 1.170387 1.082541
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 17"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 1 0 0
## Medio 8 45 15 0
## Alto 0 0 103 18
## Excelente 0 0 15 115
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.39
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7544
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.72414 0.9783 0.7744 0.8647
## Specificity 0.99679 0.9220 0.9135 0.9279
## Pos Pred Value 0.95455 0.6618 0.8512 0.8846
## Neg Pred Value 0.97492 0.9963 0.8636 0.9147
## Prevalence 0.08504 0.1349 0.3900 0.3900
## Detection Rate 0.06158 0.1320 0.3021 0.3372
## Detection Prevalence 0.06452 0.1994 0.3548 0.3812
## Balanced Accuracy 0.86047 0.9501 0.8439 0.8963
## [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 18"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 11 0 0 0
## Medio 6 44 12 0
## Alto 0 0 108 22
## Excelente 0 0 17 121
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7436
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.64706 1.0000 0.7883 0.8462
## Specificity 1.00000 0.9394 0.8922 0.9141
## Pos Pred Value 1.00000 0.7097 0.8308 0.8768
## Neg Pred Value 0.98182 1.0000 0.8626 0.8916
## Prevalence 0.04985 0.1290 0.4018 0.4194
## Detection Rate 0.03226 0.1290 0.3167 0.3548
## Detection Prevalence 0.03226 0.1818 0.3812 0.4047
## Balanced Accuracy 0.82353 0.9697 0.8402 0.8801
## [1] "VARIABLES:A7,A64,A24,A64"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.57996 -0.26471 -0.06332 0.26904 0.64635
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.4829 1.4086 63.525 < 2e-16 ***
## A7 22.4379 5.9236 3.788 0.00259 **
## A64 -0.4121 0.1562 -2.638 0.02164 *
## A24 -1.0793 0.2802 -3.852 0.00230 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4121 on 12 degrees of freedom
## Multiple R-squared: 0.8416, Adjusted R-squared: 0.802
## F-statistic: 21.25 on 3 and 12 DF, p-value: 4.307e-05
##
## A7 A64 A24
## 1.317131 1.158624 1.189450
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 19"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 4 0 0
## Medio 8 39 10 1
## Alto 0 0 117 19
## Excelente 0 0 11 112
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7686
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 0.9070 0.8478 0.8485
## Specificity 0.98722 0.9362 0.9064 0.9474
## Pos Pred Value 0.83333 0.6724 0.8603 0.9106
## Neg Pred Value 0.97476 0.9859 0.8976 0.9083
## Prevalence 0.08211 0.1261 0.4047 0.3871
## Detection Rate 0.05865 0.1144 0.3431 0.3284
## Detection Prevalence 0.07038 0.1701 0.3988 0.3607
## Balanced Accuracy 0.85075 0.9216 0.8771 0.8979
## [1] "VARIABLES:A7,A64,A30,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6741 -0.1621 0.0093 0.2009 0.5117
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 88.9232 1.1474 77.497 < 2e-16 ***
## A7 18.3422 5.1700 3.548 0.004569 **
## A64 -0.2452 0.1268 -1.934 0.079220 .
## A30 -1.7652 0.3334 -5.295 0.000255 ***
## A77 1.3288 0.7570 1.755 0.106960
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3395 on 11 degrees of freedom
## Multiple R-squared: 0.9014, Adjusted R-squared: 0.8656
## F-statistic: 25.15 on 4 and 11 DF, p-value: 1.74e-05
##
## A7 A64 A30 A77
## 1.478125 1.124819 1.470754 1.063996
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 20"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 3 0 1
## Medio 7 36 14 0
## Alto 0 0 126 25
## Excelente 0 0 2 105
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7722
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75862 0.9231 0.8873 0.8015
## Specificity 0.98718 0.9305 0.8744 0.9905
## Pos Pred Value 0.84615 0.6316 0.8344 0.9813
## Neg Pred Value 0.97778 0.9894 0.9158 0.8889
## Prevalence 0.08504 0.1144 0.4164 0.3842
## Detection Rate 0.06452 0.1056 0.3695 0.3079
## Detection Prevalence 0.07625 0.1672 0.4428 0.3138
## Balanced Accuracy 0.87290 0.9268 0.8808 0.8960
## [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 21"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 1 0 0
## Medio 5 30 8 0
## Alto 0 2 124 23
## Excelente 0 0 16 112
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.434
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.75
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80000 0.90909 0.8378 0.8296
## Specificity 0.99684 0.95779 0.8705 0.9223
## Pos Pred Value 0.95238 0.69767 0.8322 0.8750
## Neg Pred Value 0.98438 0.98993 0.8750 0.8920
## Prevalence 0.07331 0.09677 0.4340 0.3959
## Detection Rate 0.05865 0.08798 0.3636 0.3284
## Detection Prevalence 0.06158 0.12610 0.4370 0.3754
## Balanced Accuracy 0.89842 0.93344 0.8542 0.8760
## [1] "VARIABLES:A7,A7,A80,A62,A83"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81790 -0.40567 -0.06708 0.31072 0.97162
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.4520 1.1770 70.904 5.46e-16 ***
## A7 37.8489 8.1969 4.617 0.000743 ***
## A80 0.8488 0.6583 1.289 0.223689
## A62 -1.0205 1.7294 -0.590 0.567079
## A83 0.7058 1.0538 0.670 0.516792
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6111 on 11 degrees of freedom
## Multiple R-squared: 0.6807, Adjusted R-squared: 0.5647
## F-statistic: 5.864 on 4 and 11 DF, p-value: 0.00889
##
## A7 A80 A62 A83
## 1.147093 1.280371 1.240404 1.420830
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 22"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 0 0 0
## Medio 8 46 12 0
## Alto 0 0 98 18
## Excelente 0 0 14 120
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7771
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75758 1.0000 0.7903 0.8696
## Specificity 1.00000 0.9322 0.9171 0.9310
## Pos Pred Value 1.00000 0.6970 0.8448 0.8955
## Neg Pred Value 0.97468 1.0000 0.8844 0.9130
## Prevalence 0.09677 0.1349 0.3636 0.4047
## Detection Rate 0.07331 0.1349 0.2874 0.3519
## Detection Prevalence 0.07331 0.1935 0.3402 0.3930
## Balanced Accuracy 0.87879 0.9661 0.8537 0.9003
## [1] "VARIABLES:A7,A64,A24,A64"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.57996 -0.26471 -0.06332 0.26904 0.64635
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.4829 1.4086 63.525 < 2e-16 ***
## A7 22.4379 5.9236 3.788 0.00259 **
## A64 -0.4121 0.1562 -2.638 0.02164 *
## A24 -1.0793 0.2802 -3.852 0.00230 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4121 on 12 degrees of freedom
## Multiple R-squared: 0.8416, Adjusted R-squared: 0.802
## F-statistic: 21.25 on 3 and 12 DF, p-value: 4.307e-05
##
## A7 A64 A24
## 1.317131 1.158624 1.189450
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 23"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 6 40 14 0
## Alto 0 0 104 20
## Excelente 0 0 17 114
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7488
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80645 0.9756 0.7704 0.8507
## Specificity 0.99677 0.9333 0.9029 0.9179
## Pos Pred Value 0.96154 0.6667 0.8387 0.8702
## Neg Pred Value 0.98095 0.9964 0.8571 0.9048
## Prevalence 0.09091 0.1202 0.3959 0.3930
## Detection Rate 0.07331 0.1173 0.3050 0.3343
## Detection Prevalence 0.07625 0.1760 0.3636 0.3842
## Balanced Accuracy 0.90161 0.9545 0.8366 0.8843
## [1] "VARIABLES:A56,A64,A60,A7"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.95444 -0.33129 0.07095 0.41193 0.81256
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.3588 2.1570 40.037 2.86e-13 ***
## A56 -0.4794 0.5009 -0.957 0.3591
## A64 -0.2955 0.2268 -1.303 0.2191
## A60 0.5878 1.0589 0.555 0.5899
## A7 22.6082 11.5167 1.963 0.0754 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6056 on 11 degrees of freedom
## Multiple R-squared: 0.6864, Adjusted R-squared: 0.5724
## F-statistic: 6.021 on 4 and 11 DF, p-value: 0.008104
##
## A56 A64 A60 A7
## 2.288100 1.130976 1.062045 2.305606
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 24"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 1 0 0
## Medio 8 44 17 0
## Alto 0 0 105 22
## Excelente 0 0 10 112
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7508
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 0.9778 0.7955 0.8358
## Specificity 0.99678 0.9155 0.8947 0.9517
## Pos Pred Value 0.95652 0.6377 0.8268 0.9180
## Neg Pred Value 0.97484 0.9963 0.8738 0.8995
## Prevalence 0.08798 0.1320 0.3871 0.3930
## Detection Rate 0.06452 0.1290 0.3079 0.3284
## Detection Prevalence 0.06745 0.2023 0.3724 0.3578
## Balanced Accuracy 0.86506 0.9467 0.8451 0.8938
## [1] "VARIABLES:A7,A64,A35,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.5904 -0.2573 -0.1400 0.4593 0.6404
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.1030 1.2197 70.595 5.72e-16 ***
## A7 27.4956 6.4545 4.260 0.00134 **
## A64 -0.2735 0.1768 -1.547 0.15013
## A35 -22.6892 7.5644 -2.999 0.01209 *
## A77 -0.2866 1.0715 -0.268 0.79403
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4744 on 11 degrees of freedom
## Multiple R-squared: 0.8076, Adjusted R-squared: 0.7377
## F-statistic: 11.54 on 4 and 11 DF, p-value: 0.0006291
##
## A7 A64 A35 A77
## 1.180299 1.120262 1.118490 1.092069
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 25"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 4 1 0
## Medio 3 32 10 0
## Alto 0 0 114 34
## Excelente 0 0 3 116
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4399
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7567
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.88889 0.88889 0.8906 0.7733
## Specificity 0.98408 0.95738 0.8404 0.9843
## Pos Pred Value 0.82759 0.71111 0.7703 0.9748
## Neg Pred Value 0.99038 0.98649 0.9275 0.8468
## Prevalence 0.07918 0.10557 0.3754 0.4399
## Detection Rate 0.07038 0.09384 0.3343 0.3402
## Detection Prevalence 0.08504 0.13196 0.4340 0.3490
## Balanced Accuracy 0.93648 0.92313 0.8655 0.8788
## [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 26"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 10 0 0 0
## Medio 8 41 14 3
## Alto 0 0 129 31
## Excelente 0 0 5 100
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.434
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.725
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.55556 1.0000 0.8716 0.7463
## Specificity 1.00000 0.9167 0.8394 0.9758
## Pos Pred Value 1.00000 0.6212 0.8062 0.9524
## Neg Pred Value 0.97583 1.0000 0.8950 0.8559
## Prevalence 0.05279 0.1202 0.4340 0.3930
## Detection Rate 0.02933 0.1202 0.3783 0.2933
## Detection Prevalence 0.02933 0.1935 0.4692 0.3079
## Balanced Accuracy 0.77778 0.9583 0.8555 0.8611
## [1] "VARIABLES:A7,A64,A36,A20"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.88116 -0.39592 -0.07397 0.53027 0.62447
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.2845333 1.9845565 43.478 1.16e-13 ***
## A7 24.4241246 10.3188841 2.367 0.0374 *
## A64 -0.1847848 0.2443178 -0.756 0.4653
## A36 -1.1926537 1.0685160 -1.116 0.2881
## A20 0.0008873 0.1114400 0.008 0.9938
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6048 on 11 degrees of freedom
## Multiple R-squared: 0.6873, Adjusted R-squared: 0.5735
## F-statistic: 6.043 on 4 and 11 DF, p-value: 0.007998
##
## A7 A64 A36 A20
## 1.855698 1.316233 2.291421 1.278368
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 27"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 1 0 0
## Medio 10 42 12 0
## Alto 0 0 101 16
## Excelente 0 0 11 121
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7866
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.72973 0.9767 0.8145 0.8832
## Specificity 0.99671 0.9262 0.9263 0.9461
## Pos Pred Value 0.96429 0.6562 0.8632 0.9167
## Neg Pred Value 0.96805 0.9964 0.8973 0.9234
## Prevalence 0.10850 0.1261 0.3636 0.4018
## Detection Rate 0.07918 0.1232 0.2962 0.3548
## Detection Prevalence 0.08211 0.1877 0.3431 0.3871
## Balanced Accuracy 0.86322 0.9515 0.8704 0.9146
## [1] "VARIABLES:A7,A64,A7,A35"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.5771 -0.3055 -0.1238 0.4622 0.6444
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.8846 0.8704 98.675 < 2e-16 ***
## A7 27.7529 6.1306 4.527 0.000693 ***
## A64 -0.2773 0.1693 -1.638 0.127267
## A35 -22.1754 7.0278 -3.155 0.008291 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4556 on 12 degrees of freedom
## Multiple R-squared: 0.8064, Adjusted R-squared: 0.758
## F-statistic: 16.66 on 3 and 12 DF, p-value: 0.0001412
##
## A7 A64 A35
## 1.154082 1.112957 1.046384
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 28"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 5 49 11 0
## Alto 0 0 95 18
## Excelente 0 0 21 120
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7527
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80000 0.9608 0.7480 0.8696
## Specificity 0.99367 0.9448 0.9159 0.8966
## Pos Pred Value 0.90909 0.7538 0.8407 0.8511
## Neg Pred Value 0.98433 0.9928 0.8596 0.9100
## Prevalence 0.07331 0.1496 0.3724 0.4047
## Detection Rate 0.05865 0.1437 0.2786 0.3519
## Detection Prevalence 0.06452 0.1906 0.3314 0.4135
## Balanced Accuracy 0.89684 0.9528 0.8320 0.8831
## [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 29"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 0 0 0
## Medio 5 47 11 0
## Alto 0 0 107 14
## Excelente 0 0 17 119
##
## Overall Statistics
##
## Accuracy : 0.8622
## 95% CI : (0.821, 0.8969)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7954
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80769 1.0000 0.7926 0.8947
## Specificity 1.00000 0.9456 0.9320 0.9183
## Pos Pred Value 1.00000 0.7460 0.8843 0.8750
## Neg Pred Value 0.98438 1.0000 0.8727 0.9317
## Prevalence 0.07625 0.1378 0.3959 0.3900
## Detection Rate 0.06158 0.1378 0.3138 0.3490
## Detection Prevalence 0.06158 0.1848 0.3548 0.3988
## Balanced Accuracy 0.90385 0.9728 0.8623 0.9065
## [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 30"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 3 0 0
## Medio 4 48 12 1
## Alto 0 0 104 20
## Excelente 0 0 9 122
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.4194
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7865
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.81818 0.9412 0.8320 0.8531
## Specificity 0.99060 0.9414 0.9074 0.9545
## Pos Pred Value 0.85714 0.7385 0.8387 0.9313
## Neg Pred Value 0.98750 0.9891 0.9032 0.9000
## Prevalence 0.06452 0.1496 0.3666 0.4194
## Detection Rate 0.05279 0.1408 0.3050 0.3578
## Detection Prevalence 0.06158 0.1906 0.3636 0.3842
## Balanced Accuracy 0.90439 0.9413 0.8697 0.9038
## [1] "VARIABLES:A7,A64,A36,A38,A48"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85983 -0.39512 -0.08864 0.51005 0.61548
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.14945 1.95362 44.097 8.65e-13 ***
## A7 24.79960 10.49643 2.363 0.0398 *
## A64 -0.20004 0.29549 -0.677 0.5138
## A36 -1.17612 1.06921 -1.100 0.2971
## A38 0.01608 0.08264 0.195 0.8496
## A48 -0.05141 0.77464 -0.066 0.9484
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6328 on 10 degrees of freedom
## Multiple R-squared: 0.6888, Adjusted R-squared: 0.5332
## F-statistic: 4.427 on 5 and 10 DF, p-value: 0.02185
##
## A7 A64 A36 A38 A48
## 1.754262 1.758998 2.096244 1.084097 1.884055
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 31"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 28 7 0 0
## Medio 3 36 7 2
## Alto 0 0 101 24
## Excelente 0 0 17 116
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7398
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90323 0.8372 0.8080 0.8169
## Specificity 0.97742 0.9597 0.8889 0.9146
## Pos Pred Value 0.80000 0.7500 0.8080 0.8722
## Neg Pred Value 0.99020 0.9761 0.8889 0.8750
## Prevalence 0.09091 0.1261 0.3666 0.4164
## Detection Rate 0.08211 0.1056 0.2962 0.3402
## Detection Prevalence 0.10264 0.1408 0.3666 0.3900
## Balanced Accuracy 0.94032 0.8985 0.8484 0.8657
## [1] "VARIABLES:A7,A64,A25,A60"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.71951 -0.23334 0.06127 0.17938 0.61161
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.2637 1.3604 65.614 1.28e-15 ***
## A7 25.8040 5.4523 4.733 0.000617 ***
## A64 -0.4396 0.1519 -2.893 0.014618 *
## A25 -1.2986 0.3183 -4.080 0.001820 **
## A60 0.3691 0.6926 0.533 0.604691
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3976 on 11 degrees of freedom
## Multiple R-squared: 0.8649, Adjusted R-squared: 0.8157
## F-statistic: 17.6 on 4 and 11 DF, p-value: 9.538e-05
##
## A7 A64 A25 A60
## 1.198975 1.177909 1.102491 1.054179
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 32"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 2 0 5
## Medio 6 55 15 5
## Alto 0 2 96 19
## Excelente 0 0 11 106
##
## Overall Statistics
##
## Accuracy : 0.8094
## 95% CI : (0.7636, 0.8497)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7256
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76000 0.9322 0.7869 0.7852
## Specificity 0.97785 0.9078 0.9041 0.9466
## Pos Pred Value 0.73077 0.6790 0.8205 0.9060
## Neg Pred Value 0.98095 0.9846 0.8839 0.8705
## Prevalence 0.07331 0.1730 0.3578 0.3959
## Detection Rate 0.05572 0.1613 0.2815 0.3109
## Detection Prevalence 0.07625 0.2375 0.3431 0.3431
## Balanced Accuracy 0.86892 0.9200 0.8455 0.8659
## [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 33"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 1
## Medio 6 41 11 0
## Alto 0 2 125 18
## Excelente 0 0 13 98
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.437
## 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 0.80645 0.9318 0.8389 0.8376
## Specificity 0.99355 0.9428 0.8958 0.9420
## Pos Pred Value 0.92593 0.7069 0.8621 0.8829
## Neg Pred Value 0.98089 0.9894 0.8776 0.9174
## Prevalence 0.09091 0.1290 0.4370 0.3431
## Detection Rate 0.07331 0.1202 0.3666 0.2874
## Detection Prevalence 0.07918 0.1701 0.4252 0.3255
## Balanced Accuracy 0.90000 0.9373 0.8674 0.8898
## [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 34"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 2 0 0
## Medio 5 31 13 4
## Alto 0 0 118 17
## Excelente 0 0 12 116
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4194
## 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 0.82143 0.93939 0.8252 0.8467
## Specificity 0.99361 0.92857 0.9141 0.9412
## Pos Pred Value 0.92000 0.58491 0.8741 0.9062
## Neg Pred Value 0.98418 0.99306 0.8786 0.9014
## Prevalence 0.08211 0.09677 0.4194 0.4018
## Detection Rate 0.06745 0.09091 0.3460 0.3402
## Detection Prevalence 0.07331 0.15543 0.3959 0.3754
## Balanced Accuracy 0.90752 0.93398 0.8697 0.8939
## [1] "VARIABLES:A7,A64,A36,A67"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85794 -0.39791 -0.02883 0.48355 0.62400
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 86.3941 1.6081 53.723 1.15e-14 ***
## A7 25.3489 9.9879 2.538 0.0276 *
## A64 -0.1681 0.2415 -0.696 0.5009
## A36 -1.2019 0.9793 -1.227 0.2453
## A67 -0.5459 1.1507 -0.474 0.6445
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5987 on 11 degrees of freedom
## Multiple R-squared: 0.6935, Adjusted R-squared: 0.5821
## F-statistic: 6.223 on 4 and 11 DF, p-value: 0.007207
##
## A7 A64 A36 A67
## 1.774135 1.312303 1.964286 1.074908
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 35"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 0 0 0
## Medio 8 34 7 0
## Alto 0 11 125 26
## Excelente 0 0 5 106
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7466
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.70370 0.75556 0.9124 0.8030
## Specificity 1.00000 0.94932 0.8186 0.9761
## Pos Pred Value 1.00000 0.69388 0.7716 0.9550
## Neg Pred Value 0.97516 0.96233 0.9330 0.8870
## Prevalence 0.07918 0.13196 0.4018 0.3871
## Detection Rate 0.05572 0.09971 0.3666 0.3109
## Detection Prevalence 0.05572 0.14370 0.4751 0.3255
## Balanced Accuracy 0.85185 0.85244 0.8655 0.8896
## [1] "VARIABLES:A7,A7,A6,A25"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6672 -0.2837 -0.0867 0.1987 0.9951
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 87.6230 1.3914 62.973 < 2e-16 ***
## A7 35.3305 6.3895 5.529 0.00013 ***
## A6 -0.2955 0.1970 -1.500 0.15952
## A25 -1.0639 0.3613 -2.945 0.01226 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4646 on 12 degrees of freedom
## Multiple R-squared: 0.7986, Adjusted R-squared: 0.7483
## F-statistic: 15.86 on 3 and 12 DF, p-value: 0.0001778
##
## A7 A6 A25
## 1.205503 1.173175 1.039947
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 36"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 28 2 0 0
## Medio 6 29 13 1
## Alto 0 0 120 13
## Excelente 0 0 14 115
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.4311
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7845
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82353 0.93548 0.8163 0.8915
## Specificity 0.99349 0.93548 0.9330 0.9340
## Pos Pred Value 0.93333 0.59184 0.9023 0.8915
## Neg Pred Value 0.98071 0.99315 0.8702 0.9340
## Prevalence 0.09971 0.09091 0.4311 0.3783
## Detection Rate 0.08211 0.08504 0.3519 0.3372
## Detection Prevalence 0.08798 0.14370 0.3900 0.3783
## Balanced Accuracy 0.90851 0.93548 0.8747 0.9127
## [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 37"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 1
## Medio 6 49 14 1
## Alto 0 0 109 25
## Excelente 0 0 13 99
##
## Overall Statistics
##
## Accuracy : 0.8182
## 95% CI : (0.7731, 0.8577)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7346
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78571 0.9608 0.8015 0.7857
## Specificity 0.99042 0.9276 0.8780 0.9395
## Pos Pred Value 0.88000 0.7000 0.8134 0.8839
## Neg Pred Value 0.98101 0.9926 0.8696 0.8821
## Prevalence 0.08211 0.1496 0.3988 0.3695
## Detection Rate 0.06452 0.1437 0.3196 0.2903
## Detection Prevalence 0.07331 0.2053 0.3930 0.3284
## Balanced Accuracy 0.88806 0.9442 0.8398 0.8626
## [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 27 3 0 0
## Medio 3 41 19 1
## Alto 0 0 111 27
## Excelente 0 0 15 94
##
## Overall Statistics
##
## Accuracy : 0.8006
## 95% CI : (0.7542, 0.8417)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7074
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90000 0.9318 0.7655 0.7705
## Specificity 0.99035 0.9226 0.8622 0.9315
## Pos Pred Value 0.90000 0.6406 0.8043 0.8624
## Neg Pred Value 0.99035 0.9892 0.8325 0.8793
## Prevalence 0.08798 0.1290 0.4252 0.3578
## Detection Rate 0.07918 0.1202 0.3255 0.2757
## Detection Prevalence 0.08798 0.1877 0.4047 0.3196
## Balanced Accuracy 0.94518 0.9272 0.8139 0.8510
## [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 39"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 16 1 0 0
## Medio 10 48 18 0
## Alto 0 0 99 16
## Excelente 0 0 11 122
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7584
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.61538 0.9796 0.7734 0.8841
## Specificity 0.99683 0.9041 0.9249 0.9458
## Pos Pred Value 0.94118 0.6316 0.8609 0.9173
## Neg Pred Value 0.96914 0.9962 0.8717 0.9231
## Prevalence 0.07625 0.1437 0.3754 0.4047
## Detection Rate 0.04692 0.1408 0.2903 0.3578
## Detection Prevalence 0.04985 0.2229 0.3372 0.3900
## Balanced Accuracy 0.80611 0.9419 0.8492 0.9149
## [1] "VARIABLES:A7,A64,A82,A30"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.58858 -0.20604 -0.00298 0.32972 0.50788
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.20856 1.30721 68.244 8.3e-16 ***
## A7 18.87537 5.78733 3.262 0.00758 **
## A64 -0.28358 0.16254 -1.745 0.10888
## A82 0.05084 0.08196 0.620 0.54765
## A30 -1.53294 0.40826 -3.755 0.00318 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3776 on 11 degrees of freedom
## Multiple R-squared: 0.8781, Adjusted R-squared: 0.8338
## F-statistic: 19.81 on 4 and 11 DF, p-value: 5.479e-05
##
## A7 A64 A82 A30
## 1.497513 1.494593 1.545859 1.783113
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 40"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 5 0 0
## Medio 4 38 10 0
## Alto 0 0 118 16
## Excelente 0 0 17 106
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7745
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.87097 0.8837 0.8138 0.8689
## Specificity 0.98387 0.9530 0.9184 0.9224
## Pos Pred Value 0.84375 0.7308 0.8806 0.8618
## Neg Pred Value 0.98706 0.9827 0.8696 0.9266
## Prevalence 0.09091 0.1261 0.4252 0.3578
## Detection Rate 0.07918 0.1114 0.3460 0.3109
## Detection Prevalence 0.09384 0.1525 0.3930 0.3607
## Balanced Accuracy 0.92742 0.9184 0.8661 0.8956
## [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 41"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 16 3 0 0
## Medio 5 47 12 2
## Alto 0 0 118 23
## Excelente 0 0 12 103
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7503
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76190 0.9400 0.8310 0.8047
## Specificity 0.99062 0.9347 0.8844 0.9437
## Pos Pred Value 0.84211 0.7121 0.8369 0.8957
## Neg Pred Value 0.98447 0.9891 0.8800 0.8894
## Prevalence 0.06158 0.1466 0.4164 0.3754
## Detection Rate 0.04692 0.1378 0.3460 0.3021
## Detection Prevalence 0.05572 0.1935 0.4135 0.3372
## Balanced Accuracy 0.87626 0.9374 0.8577 0.8742
## [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 42"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 2 0 0
## Medio 6 41 11 0
## Alto 0 4 109 30
## Excelente 0 0 9 110
##
## Overall Statistics
##
## Accuracy : 0.8182
## 95% CI : (0.7731, 0.8577)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7287
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76000 0.8723 0.8450 0.7857
## Specificity 0.99367 0.9422 0.8396 0.9552
## Pos Pred Value 0.90476 0.7069 0.7622 0.9244
## Neg Pred Value 0.98125 0.9788 0.8990 0.8649
## Prevalence 0.07331 0.1378 0.3783 0.4106
## Detection Rate 0.05572 0.1202 0.3196 0.3226
## Detection Prevalence 0.06158 0.1701 0.4194 0.3490
## Balanced Accuracy 0.87684 0.9073 0.8423 0.8705
## [1] "VARIABLES:A7,A7,A33,A62,A83"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.11982 -0.21598 0.08451 0.16174 1.06846
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.5674 1.1912 71.830 4.73e-16 ***
## A7 38.4610 7.4183 5.185 0.000302 ***
## A33 -21.5949 10.1776 -2.122 0.057390 .
## A62 -4.4321 1.9668 -2.253 0.045617 *
## A83 0.3764 0.8672 0.434 0.672667
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5523 on 11 degrees of freedom
## Multiple R-squared: 0.7392, Adjusted R-squared: 0.6444
## F-statistic: 7.795 on 4 and 11 DF, p-value: 0.00312
##
## A7 A33 A62 A83
## 1.150179 1.899660 1.964067 1.177977
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 43"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 6 46 15 0
## Alto 0 0 110 17
## Excelente 0 0 9 116
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7881
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76923 0.9583 0.8209 0.8722
## Specificity 0.99365 0.9283 0.9179 0.9567
## Pos Pred Value 0.90909 0.6866 0.8661 0.9280
## Neg Pred Value 0.98119 0.9927 0.8879 0.9213
## Prevalence 0.07625 0.1408 0.3930 0.3900
## Detection Rate 0.05865 0.1349 0.3226 0.3402
## Detection Prevalence 0.06452 0.1965 0.3724 0.3666
## Balanced Accuracy 0.88144 0.9433 0.8694 0.9145
## [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 44"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 1 0 0
## Medio 11 32 11 1
## Alto 0 0 110 20
## Excelente 0 0 16 113
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7389
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.70270 0.96970 0.8029 0.8433
## Specificity 0.99671 0.92532 0.9020 0.9227
## Pos Pred Value 0.96296 0.58182 0.8462 0.8760
## Neg Pred Value 0.96497 0.99650 0.8720 0.9009
## Prevalence 0.10850 0.09677 0.4018 0.3930
## Detection Rate 0.07625 0.09384 0.3226 0.3314
## Detection Prevalence 0.07918 0.16129 0.3812 0.3783
## Balanced Accuracy 0.84971 0.94751 0.8524 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 45"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 1 0 1
## Medio 6 38 14 0
## Alto 0 0 123 23
## Excelente 0 0 10 106
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4311
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7563
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76000 0.9744 0.8367 0.8154
## Specificity 0.99367 0.9338 0.8814 0.9526
## Pos Pred Value 0.90476 0.6552 0.8425 0.9138
## Neg Pred Value 0.98125 0.9965 0.8769 0.8933
## Prevalence 0.07331 0.1144 0.4311 0.3812
## Detection Rate 0.05572 0.1114 0.3607 0.3109
## Detection Prevalence 0.06158 0.1701 0.4282 0.3402
## Balanced Accuracy 0.87684 0.9541 0.8591 0.8840
## [1] "VARIABLES:A7,A64,A6,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0485 -0.3310 0.1254 0.3232 0.6875
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.9660 1.3651 62.240 2.28e-15 ***
## A7 35.7489 8.0670 4.432 0.00101 **
## A64 -0.3318 0.2160 -1.536 0.15273
## A6 -0.4108 0.2597 -1.582 0.14198
## A77 -0.1691 1.3362 -0.127 0.90158
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5773 on 11 degrees of freedom
## Multiple R-squared: 0.7151, Adjusted R-squared: 0.6115
## F-statistic: 6.902 on 4 and 11 DF, p-value: 0.004944
##
## A7 A64 A6 A77
## 1.244909 1.128877 1.320724 1.146892
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 46"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 2 0 0
## Medio 3 47 11 0
## Alto 0 0 112 32
## Excelente 0 0 7 107
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7602
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.86957 0.9592 0.8615 0.7698
## Specificity 0.99371 0.9521 0.8483 0.9653
## Pos Pred Value 0.90909 0.7705 0.7778 0.9386
## Neg Pred Value 0.99060 0.9929 0.9086 0.8590
## Prevalence 0.06745 0.1437 0.3812 0.4076
## Detection Rate 0.05865 0.1378 0.3284 0.3138
## Detection Prevalence 0.06452 0.1789 0.4223 0.3343
## Balanced Accuracy 0.93164 0.9556 0.8549 0.8676
## [1] "VARIABLES:A7,A64,A80,A20"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.90718 -0.40830 0.02072 0.48765 0.80315
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.19954 1.26076 66.785 1.05e-15 ***
## A7 31.98144 7.95788 4.019 0.00202 **
## A64 -0.23096 0.23466 -0.984 0.34616
## A80 0.68283 0.57544 1.187 0.26037
## A20 0.04735 0.10249 0.462 0.65312
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6008 on 11 degrees of freedom
## Multiple R-squared: 0.6913, Adjusted R-squared: 0.5791
## F-statistic: 6.16 on 4 and 11 DF, p-value: 0.007474
##
## A7 A64 A80 A20
## 1.118284 1.230358 1.011962 1.095701
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 47"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 1 0 0
## Medio 9 30 3 0
## Alto 0 10 128 21
## Excelente 0 0 8 110
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7677
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.70000 0.73171 0.9209 0.8397
## Specificity 0.99678 0.96000 0.8465 0.9619
## Pos Pred Value 0.95455 0.71429 0.8050 0.9322
## Neg Pred Value 0.97179 0.96321 0.9396 0.9058
## Prevalence 0.08798 0.12023 0.4076 0.3842
## Detection Rate 0.06158 0.08798 0.3754 0.3226
## Detection Prevalence 0.06452 0.12317 0.4663 0.3460
## Balanced Accuracy 0.84839 0.84585 0.8837 0.9008
## [1] "VARIABLES:A7,A7,A35,A62"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6418 -0.2397 -0.1341 0.3247 0.9175
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.2070 0.8704 97.891 < 2e-16 ***
## A7 32.2097 6.6486 4.845 0.000402 ***
## A35 -21.2526 7.8362 -2.712 0.018881 *
## A62 -0.9113 1.3372 -0.682 0.508480
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4946 on 12 degrees of freedom
## Multiple R-squared: 0.7719, Adjusted R-squared: 0.7148
## F-statistic: 13.53 on 3 and 12 DF, p-value: 0.0003707
##
## A7 A35 A62
## 1.152152 1.104273 1.132132
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 48"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 1 0 0
## Medio 8 37 13 0
## Alto 0 0 107 19
## Excelente 0 0 13 119
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7648
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9737 0.8045 0.8623
## Specificity 0.99676 0.9307 0.9087 0.9360
## Pos Pred Value 0.96000 0.6379 0.8492 0.9015
## Neg Pred Value 0.97468 0.9965 0.8791 0.9091
## Prevalence 0.09384 0.1114 0.3900 0.4047
## Detection Rate 0.07038 0.1085 0.3138 0.3490
## Detection Prevalence 0.07331 0.1701 0.3695 0.3871
## Balanced Accuracy 0.87338 0.9522 0.8566 0.8991
## [1] "VARIABLES:A56,A64,A6,A7"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74432 -0.29692 -0.00665 0.33673 0.55645
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.1588 1.6364 54.485 9.81e-15 ***
## A56 -1.2033 0.4049 -2.972 0.01270 *
## A64 -0.3390 0.1609 -2.107 0.05884 .
## A6 -0.7110 0.2105 -3.377 0.00617 **
## A7 18.9118 8.2567 2.290 0.04274 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4302 on 11 degrees of freedom
## Multiple R-squared: 0.8417, Adjusted R-squared: 0.7842
## F-statistic: 14.63 on 4 and 11 DF, p-value: 0.0002223
##
## A56 A64 A6 A7
## 2.961905 1.127734 1.562622 2.347983
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 49"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 3 0 0
## Medio 3 46 9 2
## Alto 0 0 113 9
## Excelente 0 0 15 112
##
## Overall Statistics
##
## Accuracy : 0.8798
## 95% CI : (0.8404, 0.9123)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8252
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90625 0.9388 0.8248 0.9106
## Specificity 0.99029 0.9521 0.9559 0.9312
## Pos Pred Value 0.90625 0.7667 0.9262 0.8819
## Neg Pred Value 0.99029 0.9893 0.8904 0.9486
## Prevalence 0.09384 0.1437 0.4018 0.3607
## Detection Rate 0.08504 0.1349 0.3314 0.3284
## Detection Prevalence 0.09384 0.1760 0.3578 0.3724
## Balanced Accuracy 0.94827 0.9454 0.8903 0.9209
## [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 50"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 0 0 0
## Medio 6 42 13 0
## Alto 0 0 93 24
## Excelente 0 0 24 113
##
## Overall Statistics
##
## Accuracy : 0.8035
## 95% CI : (0.7573, 0.8444)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7105
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.81250 1.0000 0.7154 0.8248
## Specificity 1.00000 0.9365 0.8863 0.8824
## Pos Pred Value 1.00000 0.6885 0.7949 0.8248
## Neg Pred Value 0.98095 1.0000 0.8348 0.8824
## Prevalence 0.09384 0.1232 0.3812 0.4018
## Detection Rate 0.07625 0.1232 0.2727 0.3314
## Detection Prevalence 0.07625 0.1789 0.3431 0.4018
## Balanced Accuracy 0.90625 0.9682 0.8008 0.8536
## [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 51"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 0 1 2
## Medio 4 38 13 0
## Alto 0 0 112 17
## Excelente 0 0 13 118
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7803
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.85185 1.0000 0.8058 0.8613
## Specificity 0.99045 0.9439 0.9158 0.9363
## Pos Pred Value 0.88462 0.6909 0.8682 0.9008
## Neg Pred Value 0.98730 1.0000 0.8726 0.9095
## Prevalence 0.07918 0.1114 0.4076 0.4018
## Detection Rate 0.06745 0.1114 0.3284 0.3460
## Detection Prevalence 0.07625 0.1613 0.3783 0.3842
## Balanced Accuracy 0.92115 0.9719 0.8608 0.8988
## [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 52"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 5 0 0
## Medio 6 43 12 0
## Alto 0 0 107 15
## Excelente 0 0 15 115
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7721
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.79310 0.8958 0.7985 0.8846
## Specificity 0.98397 0.9386 0.9275 0.9289
## Pos Pred Value 0.82143 0.7049 0.8770 0.8846
## Neg Pred Value 0.98083 0.9821 0.8767 0.9289
## Prevalence 0.08504 0.1408 0.3930 0.3812
## Detection Rate 0.06745 0.1261 0.3138 0.3372
## Detection Prevalence 0.08211 0.1789 0.3578 0.3812
## Balanced Accuracy 0.88854 0.9172 0.8630 0.9068
## [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 53"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 1 0 0
## Medio 10 43 12 0
## Alto 0 0 108 13
## Excelente 0 0 15 116
##
## Overall Statistics
##
## Accuracy : 0.8504
## 95% CI : (0.8081, 0.8866)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.781
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.69697 0.9773 0.8000 0.8992
## Specificity 0.99675 0.9259 0.9369 0.9292
## Pos Pred Value 0.95833 0.6615 0.8926 0.8855
## Neg Pred Value 0.96845 0.9964 0.8773 0.9381
## Prevalence 0.09677 0.1290 0.3959 0.3783
## Detection Rate 0.06745 0.1261 0.3167 0.3402
## Detection Prevalence 0.07038 0.1906 0.3548 0.3842
## Balanced Accuracy 0.84686 0.9516 0.8684 0.9142
## [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 54"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 9 0 0
## Medio 2 35 15 0
## Alto 0 0 110 17
## Excelente 0 0 12 119
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7597
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.91667 0.7955 0.8029 0.8750
## Specificity 0.97161 0.9428 0.9167 0.9415
## Pos Pred Value 0.70968 0.6731 0.8661 0.9084
## Neg Pred Value 0.99355 0.9689 0.8738 0.9190
## Prevalence 0.07038 0.1290 0.4018 0.3988
## Detection Rate 0.06452 0.1026 0.3226 0.3490
## Detection Prevalence 0.09091 0.1525 0.3724 0.3842
## Balanced Accuracy 0.94414 0.8691 0.8598 0.9082
## [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 55"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 0 0 0
## Medio 8 43 16 1
## Alto 0 2 108 17
## Excelente 0 0 13 113
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7532
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 0.9556 0.7883 0.8626
## Specificity 1.00000 0.9155 0.9069 0.9381
## Pos Pred Value 1.00000 0.6324 0.8504 0.8968
## Neg Pred Value 0.97508 0.9927 0.8645 0.9163
## Prevalence 0.08211 0.1320 0.4018 0.3842
## Detection Rate 0.05865 0.1261 0.3167 0.3314
## Detection Prevalence 0.05865 0.1994 0.3724 0.3695
## Balanced Accuracy 0.85714 0.9355 0.8476 0.9003
## [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 56"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 2 0 0
## Medio 8 43 14 3
## Alto 0 0 108 20
## Excelente 0 0 14 105
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7392
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9556 0.7941 0.8203
## Specificity 0.99353 0.9155 0.9024 0.9343
## Pos Pred Value 0.92308 0.6324 0.8438 0.8824
## Neg Pred Value 0.97460 0.9927 0.8685 0.8964
## Prevalence 0.09384 0.1320 0.3988 0.3754
## Detection Rate 0.07038 0.1261 0.3167 0.3079
## Detection Prevalence 0.07625 0.1994 0.3754 0.3490
## Balanced Accuracy 0.87176 0.9355 0.8483 0.8773
## [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 57"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 1 0 0
## Medio 6 37 14 0
## Alto 0 0 106 10
## Excelente 0 0 20 125
##
## Overall Statistics
##
## Accuracy : 0.8504
## 95% CI : (0.8081, 0.8866)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7761
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78571 0.9737 0.7571 0.9259
## Specificity 0.99681 0.9340 0.9502 0.9029
## Pos Pred Value 0.95652 0.6491 0.9138 0.8621
## Neg Pred Value 0.98113 0.9965 0.8489 0.9490
## Prevalence 0.08211 0.1114 0.4106 0.3959
## Detection Rate 0.06452 0.1085 0.3109 0.3666
## Detection Prevalence 0.06745 0.1672 0.3402 0.4252
## Balanced Accuracy 0.89126 0.9538 0.8537 0.9144
## [1] "VARIABLES:A7,A64,A60,A9"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9188 -0.4171 0.1115 0.4526 0.7731
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.1049 1.2912 65.913 1.22e-15 ***
## A7 30.9911 8.2368 3.763 0.00314 **
## A64 -0.3599 0.2366 -1.521 0.15650
## A60 0.5393 1.0866 0.496 0.62944
## A9 -3.0416 3.7003 -0.822 0.42855
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6118 on 11 degrees of freedom
## Multiple R-squared: 0.68, Adjusted R-squared: 0.5636
## F-statistic: 5.844 on 4 and 11 DF, p-value: 0.008997
##
## A7 A64 A60 A9
## 1.155574 1.206513 1.095654 1.166914
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 58"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 5 0 0
## Medio 4 42 13 4
## Alto 0 0 118 26
## Excelente 0 0 4 108
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7551
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.80952 0.8936 0.8741 0.7826
## Specificity 0.98438 0.9286 0.8738 0.9803
## Pos Pred Value 0.77273 0.6667 0.8194 0.9643
## Neg Pred Value 0.98746 0.9820 0.9137 0.8690
## Prevalence 0.06158 0.1378 0.3959 0.4047
## Detection Rate 0.04985 0.1232 0.3460 0.3167
## Detection Prevalence 0.06452 0.1848 0.4223 0.3284
## Balanced Accuracy 0.89695 0.9111 0.8739 0.8815
## [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 59"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 1 0 8
## Medio 6 34 6 0
## Alto 0 7 120 33
## Excelente 0 0 5 99
##
## Overall Statistics
##
## Accuracy : 0.8065
## 95% CI : (0.7605, 0.847)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7113
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78571 0.80952 0.9160 0.7071
## Specificity 0.97125 0.95987 0.8095 0.9751
## Pos Pred Value 0.70968 0.73913 0.7500 0.9519
## Neg Pred Value 0.98065 0.97288 0.9392 0.8270
## Prevalence 0.08211 0.12317 0.3842 0.4106
## Detection Rate 0.06452 0.09971 0.3519 0.2903
## Detection Prevalence 0.09091 0.13490 0.4692 0.3050
## Balanced Accuracy 0.87848 0.88470 0.8628 0.8411
## [1] "VARIABLES:A7,A64,A80,A12,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7776 -0.4593 0.1157 0.4328 0.7876
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.87778 1.37153 61.886 2.95e-14 ***
## A7 29.26670 9.17161 3.191 0.00964 **
## A64 -0.31552 0.25248 -1.250 0.23987
## A80 0.92810 0.74955 1.238 0.24392
## A12 1.76206 2.93917 0.600 0.56217
## A38 -0.04027 0.09934 -0.405 0.69372
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6244 on 10 degrees of freedom
## Multiple R-squared: 0.697, Adjusted R-squared: 0.5454
## F-statistic: 4.6 on 5 and 10 DF, p-value: 0.0194
##
## A7 A64 A80 A12 A38
## 1.375385 1.318724 1.589775 1.666031 1.608606
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 60"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 3 0 2
## Medio 3 46 13 0
## Alto 0 0 109 27
## Excelente 0 0 19 99
##
## Overall Statistics
##
## Accuracy : 0.8035
## 95% CI : (0.7573, 0.8444)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7085
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.86957 0.9388 0.7730 0.7734
## Specificity 0.98428 0.9452 0.8650 0.9108
## Pos Pred Value 0.80000 0.7419 0.8015 0.8390
## Neg Pred Value 0.99051 0.9892 0.8439 0.8700
## Prevalence 0.06745 0.1437 0.4135 0.3754
## Detection Rate 0.05865 0.1349 0.3196 0.2903
## Detection Prevalence 0.07331 0.1818 0.3988 0.3460
## Balanced Accuracy 0.92692 0.9420 0.8190 0.8421
## [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 61"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 3 0 0
## Medio 7 38 5 1
## Alto 0 14 115 27
## Excelente 0 0 7 98
##
## Overall Statistics
##
## Accuracy : 0.8123
## 95% CI : (0.7668, 0.8524)
## No Information Rate : 0.3724
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7254
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78788 0.6909 0.9055 0.7778
## Specificity 0.99026 0.9545 0.8084 0.9674
## Pos Pred Value 0.89655 0.7451 0.7372 0.9333
## Neg Pred Value 0.97756 0.9414 0.9351 0.8814
## Prevalence 0.09677 0.1613 0.3724 0.3695
## Detection Rate 0.07625 0.1114 0.3372 0.2874
## Detection Prevalence 0.08504 0.1496 0.4575 0.3079
## Balanced Accuracy 0.88907 0.8227 0.8570 0.8726
## [1] "VARIABLES:A7,A7,A60,A33"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.20378 -0.20993 -0.02385 0.40171 1.04936
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.4926 1.2004 70.389 < 2e-16 ***
## A7 32.5101 8.1275 4.000 0.00176 **
## A60 0.9944 1.1625 0.855 0.40905
## A33 -8.4353 9.1563 -0.921 0.37506
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6274 on 12 degrees of freedom
## Multiple R-squared: 0.6329, Adjusted R-squared: 0.5411
## F-statistic: 6.897 on 3 and 12 DF, p-value: 0.005937
##
## A7 A60 A33
## 1.069971 1.192635 1.191570
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 62"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 3 0 0
## Medio 3 45 13 1
## Alto 0 0 107 25
## Excelente 0 0 12 108
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7542
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.88889 0.9375 0.8106 0.8060
## Specificity 0.99045 0.9420 0.8804 0.9420
## Pos Pred Value 0.88889 0.7258 0.8106 0.9000
## Neg Pred Value 0.99045 0.9892 0.8804 0.8824
## Prevalence 0.07918 0.1408 0.3871 0.3930
## Detection Rate 0.07038 0.1320 0.3138 0.3167
## Detection Prevalence 0.07918 0.1818 0.3871 0.3519
## Balanced Accuracy 0.93967 0.9397 0.8455 0.8740
## [1] "VARIABLES:A7,A64,A25,A57,A48"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73888 -0.18128 -0.00047 0.24434 0.61831
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.460583 1.408249 63.526 2.27e-14 ***
## A7 26.151725 5.912209 4.423 0.00129 **
## A64 -0.426462 0.197302 -2.161 0.05597 .
## A25 -1.322378 0.342735 -3.858 0.00317 **
## A57 -0.002754 0.153115 -0.018 0.98600
## A48 0.026547 0.502558 0.053 0.95891
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4222 on 10 degrees of freedom
## Multiple R-squared: 0.8614, Adjusted R-squared: 0.7921
## F-statistic: 12.43 on 5 and 10 DF, p-value: 0.0004988
##
## A7 A64 A25 A57 A48
## 1.249807 1.761105 1.133364 1.149123 1.780755
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 63"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 1 1 0
## Medio 4 48 13 1
## Alto 0 0 113 20
## Excelente 0 0 10 111
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7824
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82609 0.9796 0.8248 0.8409
## Specificity 0.99371 0.9384 0.9020 0.9522
## Pos Pred Value 0.90476 0.7273 0.8496 0.9174
## Neg Pred Value 0.98750 0.9964 0.8846 0.9045
## Prevalence 0.06745 0.1437 0.4018 0.3871
## Detection Rate 0.05572 0.1408 0.3314 0.3255
## Detection Prevalence 0.06158 0.1935 0.3900 0.3548
## Balanced Accuracy 0.90990 0.9590 0.8634 0.8965
## [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 64"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 0 0 0
## Medio 7 17 2 1
## Alto 0 17 120 20
## Excelente 0 0 17 123
##
## Overall Statistics
##
## Accuracy : 0.8123
## 95% CI : (0.7668, 0.8524)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7009
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.70833 0.50000 0.8633 0.8542
## Specificity 1.00000 0.96743 0.8168 0.9137
## Pos Pred Value 1.00000 0.62963 0.7643 0.8786
## Neg Pred Value 0.97840 0.94586 0.8967 0.8955
## Prevalence 0.07038 0.09971 0.4076 0.4223
## Detection Rate 0.04985 0.04985 0.3519 0.3607
## Detection Prevalence 0.04985 0.07918 0.4604 0.4106
## Balanced Accuracy 0.85417 0.73371 0.8401 0.8839
## [1] "VARIABLES:A7,A7,A64,A10"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0492 -0.4230 0.1083 0.3679 0.7863
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.2200 1.0758 79.212 <2e-16 ***
## A7 26.1383 8.8569 2.951 0.0121 *
## A64 -0.3282 0.2183 -1.504 0.1585
## A10 2.2099 1.8329 1.206 0.2512
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5821 on 12 degrees of freedom
## Multiple R-squared: 0.684, Adjusted R-squared: 0.605
## F-statistic: 8.658 on 3 and 12 DF, p-value: 0.002493
##
## A7 A64 A10
## 1.475945 1.134117 1.328977
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 65"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 0
## Medio 7 45 10 0
## Alto 0 0 97 22
## Excelente 0 0 14 124
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.4282
## 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 0.73077 0.9375 0.8017 0.8493
## Specificity 0.99048 0.9420 0.9000 0.9282
## Pos Pred Value 0.86364 0.7258 0.8151 0.8986
## Neg Pred Value 0.97806 0.9892 0.8919 0.8916
## Prevalence 0.07625 0.1408 0.3548 0.4282
## Detection Rate 0.05572 0.1320 0.2845 0.3636
## Detection Prevalence 0.06452 0.1818 0.3490 0.4047
## Balanced Accuracy 0.86062 0.9397 0.8508 0.8888
## [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 66"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 2 0 0
## Medio 5 33 13 0
## Alto 0 0 112 23
## Excelente 0 0 15 109
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4106
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.747
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.85294 0.94286 0.8000 0.8258
## Specificity 0.99349 0.94118 0.8856 0.9282
## Pos Pred Value 0.93548 0.64706 0.8296 0.8790
## Neg Pred Value 0.98387 0.99310 0.8641 0.8940
## Prevalence 0.09971 0.10264 0.4106 0.3871
## Detection Rate 0.08504 0.09677 0.3284 0.3196
## Detection Prevalence 0.09091 0.14956 0.3959 0.3636
## Balanced Accuracy 0.92321 0.94202 0.8428 0.8770
## [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 67"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 18 1 0 0
## Medio 9 45 12 0
## Alto 0 0 102 15
## Excelente 0 0 17 122
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.765
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.66667 0.9783 0.7786 0.8905
## Specificity 0.99682 0.9288 0.9286 0.9167
## Pos Pred Value 0.94737 0.6818 0.8718 0.8777
## Neg Pred Value 0.97205 0.9964 0.8705 0.9257
## Prevalence 0.07918 0.1349 0.3842 0.4018
## Detection Rate 0.05279 0.1320 0.2991 0.3578
## Detection Prevalence 0.05572 0.1935 0.3431 0.4076
## Balanced Accuracy 0.83174 0.9535 0.8536 0.9036
## [1] "VARIABLES:A7,A64,A6,A15"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.97246 -0.21935 0.06448 0.21464 0.82765
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.1142 1.0019 83.954 <2e-16 ***
## A7 37.6095 7.2489 5.188 0.0003 ***
## A64 -0.1689 0.2141 -0.789 0.4468
## A6 -0.2636 0.2318 -1.137 0.2795
## A15 1.2460 0.7248 1.719 0.1135
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5129 on 11 degrees of freedom
## Multiple R-squared: 0.7751, Adjusted R-squared: 0.6933
## F-statistic: 9.478 on 4 and 11 DF, p-value: 0.001436
##
## A7 A64 A6 A15
## 1.273484 1.405800 1.332548 1.364081
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 68"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 17 0 0 0
## Medio 8 35 14 1
## Alto 0 0 117 18
## Excelente 0 0 16 115
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4311
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7457
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.68000 1.0000 0.7959 0.8582
## Specificity 1.00000 0.9248 0.9072 0.9227
## Pos Pred Value 1.00000 0.6034 0.8667 0.8779
## Neg Pred Value 0.97531 1.0000 0.8544 0.9095
## Prevalence 0.07331 0.1026 0.4311 0.3930
## Detection Rate 0.04985 0.1026 0.3431 0.3372
## Detection Prevalence 0.04985 0.1701 0.3959 0.3842
## Balanced Accuracy 0.84000 0.9624 0.8516 0.8905
## [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 69"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 16 3 0 0
## Medio 10 47 12 3
## Alto 0 0 97 18
## Excelente 0 0 18 117
##
## Overall Statistics
##
## Accuracy : 0.8123
## 95% CI : (0.7668, 0.8524)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7236
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.61538 0.9400 0.7638 0.8478
## Specificity 0.99048 0.9141 0.9159 0.9113
## Pos Pred Value 0.84211 0.6528 0.8435 0.8667
## Neg Pred Value 0.96894 0.9888 0.8673 0.8981
## Prevalence 0.07625 0.1466 0.3724 0.4047
## Detection Rate 0.04692 0.1378 0.2845 0.3431
## Detection Prevalence 0.05572 0.2111 0.3372 0.3959
## Balanced Accuracy 0.80293 0.9270 0.8398 0.8796
## [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 70"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 5 0 0
## Medio 2 46 16 0
## Alto 0 0 102 22
## Excelente 0 0 14 109
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.3871
## 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 0.92593 0.9020 0.7727 0.8321
## Specificity 0.98408 0.9379 0.8947 0.9333
## Pos Pred Value 0.83333 0.7188 0.8226 0.8862
## Neg Pred Value 0.99357 0.9819 0.8618 0.8991
## Prevalence 0.07918 0.1496 0.3871 0.3842
## Detection Rate 0.07331 0.1349 0.2991 0.3196
## Detection Prevalence 0.08798 0.1877 0.3636 0.3607
## Balanced Accuracy 0.95500 0.9199 0.8337 0.8827
## [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 71"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 4 0 0
## Medio 7 39 11 0
## Alto 0 0 116 25
## Excelente 0 0 10 104
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7536
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78125 0.9070 0.8467 0.8062
## Specificity 0.98706 0.9396 0.8775 0.9528
## Pos Pred Value 0.86207 0.6842 0.8227 0.9123
## Neg Pred Value 0.97756 0.9859 0.8950 0.8899
## Prevalence 0.09384 0.1261 0.4018 0.3783
## Detection Rate 0.07331 0.1144 0.3402 0.3050
## Detection Prevalence 0.08504 0.1672 0.4135 0.3343
## Balanced Accuracy 0.88415 0.9233 0.8621 0.8795
## [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 72"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 0
## Medio 6 27 7 1
## Alto 0 17 118 17
## Excelente 0 0 13 113
##
## Overall Statistics
##
## Accuracy : 0.8123
## 95% CI : (0.7668, 0.8524)
## No Information Rate : 0.4047
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7141
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76000 0.57447 0.8551 0.8626
## Specificity 0.99051 0.95238 0.8325 0.9381
## Pos Pred Value 0.86364 0.65854 0.7763 0.8968
## Neg Pred Value 0.98119 0.93333 0.8942 0.9163
## Prevalence 0.07331 0.13783 0.4047 0.3842
## Detection Rate 0.05572 0.07918 0.3460 0.3314
## Detection Prevalence 0.06452 0.12023 0.4457 0.3695
## Balanced Accuracy 0.87525 0.76342 0.8438 0.9003
## [1] "VARIABLES:A7,A7,A30,A12"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7330 -0.1605 -0.1169 0.1188 0.7580
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 89.2594 1.3307 67.075 < 2e-16 ***
## A7 19.8584 6.3460 3.129 0.008704 **
## A30 -1.7362 0.3986 -4.356 0.000935 ***
## A12 0.6230 1.5627 0.399 0.697151
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.407 on 12 degrees of freedom
## Multiple R-squared: 0.8455, Adjusted R-squared: 0.8068
## F-statistic: 21.89 on 3 and 12 DF, p-value: 3.718e-05
##
## A7 A30 A12
## 1.549642 1.462507 1.108349
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 73"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 13 2 0 0
## Medio 7 45 14 2
## Alto 0 3 103 15
## Excelente 0 0 17 120
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7363
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.65000 0.9000 0.7687 0.8759
## Specificity 0.99377 0.9210 0.9130 0.9167
## Pos Pred Value 0.86667 0.6618 0.8512 0.8759
## Neg Pred Value 0.97853 0.9817 0.8591 0.9167
## Prevalence 0.05865 0.1466 0.3930 0.4018
## Detection Rate 0.03812 0.1320 0.3021 0.3519
## Detection Prevalence 0.04399 0.1994 0.3548 0.4018
## Balanced Accuracy 0.82188 0.9105 0.8409 0.8963
## [1] "VARIABLES:A7,A64,A36,A82"
##
## 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
## A36 -1.1228 0.8704 -1.290 0.2235
## A82 0.1850 0.1028 1.800 0.0994 .
## ---
## 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 A36 A82
## 1.716346 1.552935 1.968240 1.227004
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 74"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 3 0 0
## Medio 6 36 13 2
## Alto 0 0 114 17
## Excelente 0 0 10 118
##
## Overall Statistics
##
## Accuracy : 0.8504
## 95% CI : (0.8081, 0.8866)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7767
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.78571 0.9231 0.8321 0.8613
## Specificity 0.99042 0.9305 0.9167 0.9510
## Pos Pred Value 0.88000 0.6316 0.8702 0.9219
## Neg Pred Value 0.98101 0.9894 0.8905 0.9108
## Prevalence 0.08211 0.1144 0.4018 0.4018
## Detection Rate 0.06452 0.1056 0.3343 0.3460
## Detection Prevalence 0.07331 0.1672 0.3842 0.3754
## Balanced Accuracy 0.88806 0.9268 0.8744 0.9061
## [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 75"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 1 0 0
## Medio 8 44 14 1
## Alto 0 0 108 24
## Excelente 0 0 12 104
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7435
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75758 0.9778 0.8060 0.8062
## Specificity 0.99675 0.9223 0.8841 0.9434
## Pos Pred Value 0.96154 0.6567 0.8182 0.8966
## Neg Pred Value 0.97460 0.9964 0.8756 0.8889
## Prevalence 0.09677 0.1320 0.3930 0.3783
## Detection Rate 0.07331 0.1290 0.3167 0.3050
## Detection Prevalence 0.07625 0.1965 0.3871 0.3402
## Balanced Accuracy 0.87716 0.9500 0.8450 0.8748
## [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 76"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 15 2 0 0
## Medio 8 47 18 1
## Alto 0 2 107 24
## Excelente 0 0 19 98
##
## Overall Statistics
##
## Accuracy : 0.783
## 95% CI : (0.7354, 0.8256)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6788
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.65217 0.9216 0.7431 0.7967
## Specificity 0.99371 0.9069 0.8680 0.9128
## Pos Pred Value 0.88235 0.6351 0.8045 0.8376
## Neg Pred Value 0.97531 0.9850 0.8221 0.8884
## Prevalence 0.06745 0.1496 0.4223 0.3607
## Detection Rate 0.04399 0.1378 0.3138 0.2874
## Detection Prevalence 0.04985 0.2170 0.3900 0.3431
## Balanced Accuracy 0.82294 0.9142 0.8055 0.8548
## [1] "VARIABLES:A7,A7,A41,A62,A83"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.17409 -0.39782 0.03609 0.38281 0.90123
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.04671 1.18711 70.799 5.54e-16 ***
## A7 36.44851 10.51903 3.465 0.00529 **
## A41 0.34515 2.60394 0.133 0.89694
## A62 -1.50808 2.29763 -0.656 0.52508
## A83 0.04424 1.15967 0.038 0.97025
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6551 on 11 degrees of freedom
## Multiple R-squared: 0.6331, Adjusted R-squared: 0.4996
## F-statistic: 4.745 on 4 and 11 DF, p-value: 0.01806
##
## A7 A41 A62 A83
## 1.643646 2.335140 1.904923 1.497232
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 77"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 30 5 0 0
## Medio 2 42 13 0
## Alto 0 0 103 18
## Excelente 0 0 19 109
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7567
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.93750 0.8936 0.7630 0.8583
## Specificity 0.98382 0.9490 0.9126 0.9112
## Pos Pred Value 0.85714 0.7368 0.8512 0.8516
## Neg Pred Value 0.99346 0.9824 0.8545 0.9155
## Prevalence 0.09384 0.1378 0.3959 0.3724
## Detection Rate 0.08798 0.1232 0.3021 0.3196
## Detection Prevalence 0.10264 0.1672 0.3548 0.3754
## Balanced Accuracy 0.96066 0.9213 0.8378 0.8847
## [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 78"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 0 1 0
## Medio 9 43 14 0
## Alto 0 2 125 11
## Excelente 0 0 16 101
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4575
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7686
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.67857 0.9556 0.8013 0.9018
## Specificity 0.99681 0.9223 0.9297 0.9301
## Pos Pred Value 0.95000 0.6515 0.9058 0.8632
## Neg Pred Value 0.97196 0.9927 0.8473 0.9509
## Prevalence 0.08211 0.1320 0.4575 0.3284
## Detection Rate 0.05572 0.1261 0.3666 0.2962
## Detection Prevalence 0.05865 0.1935 0.4047 0.3431
## Balanced Accuracy 0.83769 0.9389 0.8655 0.9160
## [1] "VARIABLES:A7,A64,A6,A44"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.75472 -0.25482 -0.01815 0.29748 0.67051
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.7801 0.8728 97.133 < 2e-16 ***
## A7 32.8542 7.0481 4.661 0.000692 ***
## A64 -0.4501 0.1937 -2.324 0.040285 *
## A6 -0.3441 0.2116 -1.627 0.132098
## A44 0.6881 0.3420 2.012 0.069352 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4939 on 11 degrees of freedom
## Multiple R-squared: 0.7914, Adjusted R-squared: 0.7156
## F-statistic: 10.44 on 4 and 11 DF, p-value: 0.0009649
##
## A7 A64 A6 A44
## 1.298158 1.240053 1.197135 1.133938
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 79"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 3 0 0
## Medio 9 39 15 0
## Alto 0 0 115 16
## Excelente 0 0 14 103
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7563
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.9286 0.7986 0.8655
## Specificity 0.99016 0.9197 0.9188 0.9369
## Pos Pred Value 0.90000 0.6190 0.8779 0.8803
## Neg Pred Value 0.97106 0.9892 0.8619 0.9286
## Prevalence 0.10557 0.1232 0.4223 0.3490
## Detection Rate 0.07918 0.1144 0.3372 0.3021
## Detection Prevalence 0.08798 0.1848 0.3842 0.3431
## Balanced Accuracy 0.87008 0.9242 0.8587 0.9012
## [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 80"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 27 4 0 0
## Medio 2 41 9 1
## Alto 0 0 105 20
## Excelente 0 0 18 114
##
## Overall Statistics
##
## Accuracy : 0.8416
## 95% CI : (0.7985, 0.8787)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.766
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.93103 0.9111 0.7955 0.8444
## Specificity 0.98718 0.9595 0.9043 0.9126
## Pos Pred Value 0.87097 0.7736 0.8400 0.8636
## Neg Pred Value 0.99355 0.9861 0.8750 0.8995
## Prevalence 0.08504 0.1320 0.3871 0.3959
## Detection Rate 0.07918 0.1202 0.3079 0.3343
## Detection Prevalence 0.09091 0.1554 0.3666 0.3871
## Balanced Accuracy 0.95911 0.9353 0.8499 0.8785
## [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 81"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 0
## Medio 8 44 17 1
## Alto 0 0 97 12
## Excelente 0 0 12 126
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7767
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 0.9565 0.7698 0.9065
## Specificity 0.99357 0.9119 0.9442 0.9406
## Pos Pred Value 0.91667 0.6286 0.8899 0.9130
## Neg Pred Value 0.97476 0.9926 0.8750 0.9360
## Prevalence 0.08798 0.1349 0.3695 0.4076
## Detection Rate 0.06452 0.1290 0.2845 0.3695
## Detection Prevalence 0.07038 0.2053 0.3196 0.4047
## Balanced Accuracy 0.86345 0.9342 0.8570 0.9235
## [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 82"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 23 3 0 0
## Medio 7 42 16 1
## Alto 0 0 107 22
## Excelente 0 0 11 109
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.393
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7423
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.76667 0.9333 0.7985 0.8258
## Specificity 0.99035 0.9189 0.8937 0.9474
## Pos Pred Value 0.88462 0.6364 0.8295 0.9083
## Neg Pred Value 0.97778 0.9891 0.8726 0.8959
## Prevalence 0.08798 0.1320 0.3930 0.3871
## Detection Rate 0.06745 0.1232 0.3138 0.3196
## Detection Prevalence 0.07625 0.1935 0.3783 0.3519
## Balanced Accuracy 0.87851 0.9261 0.8461 0.8866
## [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 83"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 0 1 0
## Medio 8 52 10 1
## Alto 0 0 116 33
## Excelente 0 0 4 96
##
## Overall Statistics
##
## Accuracy : 0.8328
## 95% CI : (0.7889, 0.8709)
## No Information Rate : 0.3842
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7555
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.71429 1.0000 0.8855 0.7385
## Specificity 0.99681 0.9343 0.8429 0.9810
## Pos Pred Value 0.95238 0.7324 0.7785 0.9600
## Neg Pred Value 0.97500 1.0000 0.9219 0.8589
## Prevalence 0.08211 0.1525 0.3842 0.3812
## Detection Rate 0.05865 0.1525 0.3402 0.2815
## Detection Prevalence 0.06158 0.2082 0.4370 0.2933
## Balanced Accuracy 0.85555 0.9671 0.8642 0.8598
## [1] "VARIABLES:A7,A64,A64,A20"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.1840 -0.4049 0.0420 0.4233 0.7140
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.54958 1.24643 67.833 < 2e-16 ***
## A7 31.68990 8.08820 3.918 0.00204 **
## A64 -0.25950 0.23736 -1.093 0.29575
## A20 0.04791 0.10422 0.460 0.65396
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.611 on 12 degrees of freedom
## Multiple R-squared: 0.6518, Adjusted R-squared: 0.5648
## F-statistic: 7.489 on 3 and 12 DF, p-value: 0.004373
##
## A7 A64 A20
## 1.117218 1.217436 1.095677
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 84"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 1
## Medio 3 55 12 1
## Alto 0 0 106 17
## Excelente 0 0 13 109
##
## Overall Statistics
##
## Accuracy : 0.8563
## 95% CI : (0.8145, 0.8918)
## No Information Rate : 0.3842
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7908
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.88000 0.9649 0.8092 0.8516
## Specificity 0.99051 0.9437 0.9190 0.9390
## Pos Pred Value 0.88000 0.7746 0.8618 0.8934
## Neg Pred Value 0.99051 0.9926 0.8853 0.9132
## Prevalence 0.07331 0.1672 0.3842 0.3754
## Detection Rate 0.06452 0.1613 0.3109 0.3196
## Detection Prevalence 0.07331 0.2082 0.3607 0.3578
## Balanced Accuracy 0.93525 0.9543 0.8641 0.8953
## [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 85"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 31 3 0 0
## Medio 3 47 11 6
## Alto 0 0 115 32
## Excelente 0 0 3 90
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.3783
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7555
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.91176 0.9400 0.8915 0.7031
## Specificity 0.99023 0.9313 0.8491 0.9859
## Pos Pred Value 0.91176 0.7015 0.7823 0.9677
## Neg Pred Value 0.99023 0.9891 0.9278 0.8468
## Prevalence 0.09971 0.1466 0.3783 0.3754
## Detection Rate 0.09091 0.1378 0.3372 0.2639
## Detection Prevalence 0.09971 0.1965 0.4311 0.2727
## Balanced Accuracy 0.95100 0.9356 0.8703 0.8445
## [1] "VARIABLES:A7,A64,A25,A38"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.71097 -0.21231 0.02245 0.18607 0.55332
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 90.80783 1.51611 59.895 3.48e-15 ***
## A7 24.70929 5.09842 4.846 0.000514 ***
## A64 -0.44761 0.14050 -3.186 0.008671 **
## A25 -1.53207 0.32497 -4.715 0.000635 ***
## A38 -0.07620 0.05168 -1.475 0.168375
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3679 on 11 degrees of freedom
## Multiple R-squared: 0.8843, Adjusted R-squared: 0.8422
## F-statistic: 21.01 on 4 and 11 DF, p-value: 4.144e-05
##
## A7 A64 A25 A38
## 1.224027 1.176146 1.341854 1.253827
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 86"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 4 0 0
## Medio 3 38 14 0
## Alto 0 0 114 18
## Excelente 0 0 14 107
##
## Overall Statistics
##
## Accuracy : 0.8446
## 95% CI : (0.8017, 0.8814)
## No Information Rate : 0.4164
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7714
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90625 0.9048 0.8028 0.8560
## Specificity 0.98706 0.9431 0.9095 0.9352
## Pos Pred Value 0.87879 0.6909 0.8636 0.8843
## Neg Pred Value 0.99026 0.9860 0.8660 0.9182
## Prevalence 0.09384 0.1232 0.4164 0.3666
## Detection Rate 0.08504 0.1114 0.3343 0.3138
## Detection Prevalence 0.09677 0.1613 0.3871 0.3548
## Balanced Accuracy 0.94665 0.9240 0.8562 0.8956
## [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 87"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 20 0 1 2
## Medio 2 44 11 0
## Alto 0 0 118 20
## Excelente 0 0 14 109
##
## Overall Statistics
##
## Accuracy : 0.8534
## 95% CI : (0.8113, 0.8892)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7794
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90909 1.0000 0.8194 0.8321
## Specificity 0.99060 0.9562 0.8985 0.9333
## Pos Pred Value 0.86957 0.7719 0.8551 0.8862
## Neg Pred Value 0.99371 1.0000 0.8719 0.8991
## Prevalence 0.06452 0.1290 0.4223 0.3842
## Detection Rate 0.05865 0.1290 0.3460 0.3196
## Detection Prevalence 0.06745 0.1672 0.4047 0.3607
## Balanced Accuracy 0.94984 0.9781 0.8590 0.8827
## [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 88"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 25 3 0 1
## Medio 5 39 17 1
## Alto 0 0 97 23
## Excelente 0 0 19 111
##
## Overall Statistics
##
## Accuracy : 0.7977
## 95% CI : (0.751, 0.839)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7028
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.83333 0.9286 0.7293 0.8162
## Specificity 0.98714 0.9231 0.8894 0.9073
## Pos Pred Value 0.86207 0.6290 0.8083 0.8538
## Neg Pred Value 0.98397 0.9892 0.8371 0.8815
## Prevalence 0.08798 0.1232 0.3900 0.3988
## Detection Rate 0.07331 0.1144 0.2845 0.3255
## Detection Prevalence 0.08504 0.1818 0.3519 0.3812
## Balanced Accuracy 0.91024 0.9258 0.8094 0.8617
## [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 89"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 0
## Medio 8 40 23 6
## Alto 0 2 95 19
## Excelente 0 0 12 112
##
## Overall Statistics
##
## Accuracy : 0.7889
## 95% CI : (0.7416, 0.831)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6935
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 0.9091 0.7308 0.8175
## Specificity 0.99357 0.8754 0.9005 0.9412
## Pos Pred Value 0.91667 0.5195 0.8190 0.9032
## Neg Pred Value 0.97476 0.9848 0.8444 0.8848
## Prevalence 0.08798 0.1290 0.3812 0.4018
## Detection Rate 0.06452 0.1173 0.2786 0.3284
## Detection Prevalence 0.07038 0.2258 0.3402 0.3636
## Balanced Accuracy 0.86345 0.8923 0.8156 0.8793
## [1] "VARIABLES:A7,A64,A10,A41"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0325 -0.2847 0.1335 0.3573 0.8734
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.7876 1.3529 62.671 2.11e-15 ***
## A7 25.1676 9.2877 2.710 0.0203 *
## A64 -0.2369 0.2782 -0.852 0.4125
## A10 2.6094 2.0196 1.292 0.2228
## A41 1.1782 2.1146 0.557 0.5886
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5996 on 11 degrees of freedom
## Multiple R-squared: 0.6927, Adjusted R-squared: 0.5809
## F-statistic: 6.198 on 4 and 11 DF, p-value: 0.007312
##
## A7 A64 A10 A41
## 1.529774 1.736288 1.520672 1.838483
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 90"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 2 0 0
## Medio 8 30 14 3
## Alto 0 0 114 25
## Excelente 0 0 13 110
##
## Overall Statistics
##
## Accuracy : 0.8094
## 95% CI : (0.7636, 0.8497)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.713
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73333 0.93750 0.8085 0.7971
## Specificity 0.99357 0.91909 0.8750 0.9360
## Pos Pred Value 0.91667 0.54545 0.8201 0.8943
## Neg Pred Value 0.97476 0.99301 0.8663 0.8716
## Prevalence 0.08798 0.09384 0.4135 0.4047
## Detection Rate 0.06452 0.08798 0.3343 0.3226
## Detection Prevalence 0.07038 0.16129 0.4076 0.3607
## Balanced Accuracy 0.86345 0.92830 0.8418 0.8665
## [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 91"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 26 3 0 0
## Medio 4 41 12 1
## Alto 0 3 115 15
## Excelente 0 0 17 104
##
## Overall Statistics
##
## Accuracy : 0.8387
## 95% CI : (0.7953, 0.8761)
## No Information Rate : 0.4223
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7626
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.86667 0.8723 0.7986 0.8667
## Specificity 0.99035 0.9422 0.9086 0.9231
## Pos Pred Value 0.89655 0.7069 0.8647 0.8595
## Neg Pred Value 0.98718 0.9788 0.8606 0.9273
## Prevalence 0.08798 0.1378 0.4223 0.3519
## Detection Rate 0.07625 0.1202 0.3372 0.3050
## Detection Prevalence 0.08504 0.1701 0.3900 0.3548
## Balanced Accuracy 0.92851 0.9073 0.8536 0.8949
## [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 92"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 28 4 0 0
## Medio 6 35 15 1
## Alto 0 0 113 21
## Excelente 0 0 11 107
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.75
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.82353 0.8974 0.8129 0.8295
## Specificity 0.98697 0.9272 0.8960 0.9481
## Pos Pred Value 0.87500 0.6140 0.8433 0.9068
## Neg Pred Value 0.98058 0.9859 0.8744 0.9013
## Prevalence 0.09971 0.1144 0.4076 0.3783
## Detection Rate 0.08211 0.1026 0.3314 0.3138
## Detection Prevalence 0.09384 0.1672 0.3930 0.3460
## Balanced Accuracy 0.90525 0.9123 0.8545 0.8888
## [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 93"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 21 5 0 0
## Medio 7 37 18 2
## Alto 0 0 105 13
## Excelente 0 0 13 120
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.3988
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7492
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.75000 0.8810 0.7721 0.8889
## Specificity 0.98403 0.9097 0.9366 0.9369
## Pos Pred Value 0.80769 0.5781 0.8898 0.9023
## Neg Pred Value 0.97778 0.9819 0.8610 0.9279
## Prevalence 0.08211 0.1232 0.3988 0.3959
## Detection Rate 0.06158 0.1085 0.3079 0.3519
## Detection Prevalence 0.07625 0.1877 0.3460 0.3900
## Balanced Accuracy 0.86701 0.8953 0.8543 0.9129
## [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 94"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 0 0 0
## Medio 11 42 13 0
## Alto 0 4 97 18
## Excelente 0 0 21 113
##
## Overall Statistics
##
## Accuracy : 0.8035
## 95% CI : (0.7573, 0.8444)
## No Information Rate : 0.3842
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7122
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.66667 0.9130 0.7405 0.8626
## Specificity 1.00000 0.9186 0.8952 0.9000
## Pos Pred Value 1.00000 0.6364 0.8151 0.8433
## Neg Pred Value 0.96552 0.9855 0.8468 0.9130
## Prevalence 0.09677 0.1349 0.3842 0.3842
## Detection Rate 0.06452 0.1232 0.2845 0.3314
## Detection Prevalence 0.06452 0.1935 0.3490 0.3930
## Balanced Accuracy 0.83333 0.9158 0.8178 0.8813
## [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 95"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 31 6 0 0
## Medio 3 27 13 0
## Alto 0 5 108 31
## Excelente 0 0 3 114
##
## Overall Statistics
##
## Accuracy : 0.8211
## 95% CI : (0.7762, 0.8603)
## No Information Rate : 0.4252
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7352
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.91176 0.71053 0.8710 0.7862
## Specificity 0.98046 0.94719 0.8341 0.9847
## Pos Pred Value 0.83784 0.62791 0.7500 0.9744
## Neg Pred Value 0.99013 0.96309 0.9188 0.8616
## Prevalence 0.09971 0.11144 0.3636 0.4252
## Detection Rate 0.09091 0.07918 0.3167 0.3343
## Detection Prevalence 0.10850 0.12610 0.4223 0.3431
## Balanced Accuracy 0.94611 0.82886 0.8525 0.8855
## [1] "VARIABLES:A7,A7,A25,A80,A83,A77"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.4330 -0.3618 -0.1069 0.3277 0.7538
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 84.23875 2.64579 31.839 2.2e-11 ***
## A7 34.79714 6.28029 5.541 0.000247 ***
## A25 -0.84587 0.44007 -1.922 0.083518 .
## A80 1.34008 0.84018 1.595 0.141800
## A83 0.08931 1.07092 0.083 0.935183
## A77 3.00130 2.25036 1.334 0.211883
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4693 on 10 degrees of freedom
## Multiple R-squared: 0.8288, Adjusted R-squared: 0.7432
## F-statistic: 9.683 on 5 and 10 DF, p-value: 0.00137
##
## A7 A25 A80 A83 A77
## 1.141611 1.512582 3.535969 2.487942 4.921492
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 96"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 29 2 0 0
## Medio 3 47 16 2
## Alto 0 0 100 19
## Excelente 0 0 14 109
##
## Overall Statistics
##
## Accuracy : 0.8358
## 95% CI : (0.7921, 0.8735)
## No Information Rate : 0.3812
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7628
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.90625 0.9592 0.7692 0.8385
## Specificity 0.99353 0.9281 0.9100 0.9336
## Pos Pred Value 0.93548 0.6912 0.8403 0.8862
## Neg Pred Value 0.99032 0.9927 0.8649 0.9037
## Prevalence 0.09384 0.1437 0.3812 0.3812
## Detection Rate 0.08504 0.1378 0.2933 0.3196
## Detection Prevalence 0.09091 0.1994 0.3490 0.3607
## Balanced Accuracy 0.94989 0.9436 0.8396 0.8861
## [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 97"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 3 0 1
## Medio 7 47 11 0
## Alto 0 0 98 19
## Excelente 0 0 19 117
##
## Overall Statistics
##
## Accuracy : 0.824
## 95% CI : (0.7794, 0.863)
## No Information Rate : 0.4018
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7404
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.73077 0.9400 0.7656 0.8540
## Specificity 0.98730 0.9381 0.9108 0.9069
## Pos Pred Value 0.82609 0.7231 0.8376 0.8603
## Neg Pred Value 0.97799 0.9891 0.8661 0.9024
## Prevalence 0.07625 0.1466 0.3754 0.4018
## Detection Rate 0.05572 0.1378 0.2874 0.3431
## Detection Prevalence 0.06745 0.1906 0.3431 0.3988
## Balanced Accuracy 0.85904 0.9391 0.8382 0.8804
## [1] "VARIABLES:A7,A64,A10,A64"
##
## Call:
## lm(formula = f, data = mm0)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0492 -0.4230 0.1083 0.3679 0.7863
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.2200 1.0758 79.212 <2e-16 ***
## A7 26.1383 8.8569 2.951 0.0121 *
## A64 -0.3282 0.2183 -1.504 0.1585
## A10 2.2099 1.8329 1.206 0.2512
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5821 on 12 degrees of freedom
## Multiple R-squared: 0.684, Adjusted R-squared: 0.605
## F-statistic: 8.658 on 3 and 12 DF, p-value: 0.002493
##
## A7 A64 A10
## 1.475945 1.134117 1.328977
## [1] "--------------------------------------------------------------------------------------"
## [1] "CORRIDA 98"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 22 6 0 0
## Medio 3 41 16 1
## Alto 0 0 103 16
## Excelente 0 0 16 117
##
## Overall Statistics
##
## Accuracy : 0.8299
## 95% CI : (0.7857, 0.8682)
## No Information Rate : 0.3959
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7491
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.88000 0.8723 0.7630 0.8731
## Specificity 0.98101 0.9320 0.9223 0.9227
## Pos Pred Value 0.78571 0.6721 0.8655 0.8797
## Neg Pred Value 0.99042 0.9786 0.8559 0.9183
## Prevalence 0.07331 0.1378 0.3959 0.3930
## Detection Rate 0.06452 0.1202 0.3021 0.3431
## Detection Prevalence 0.08211 0.1789 0.3490 0.3900
## Balanced Accuracy 0.93051 0.9022 0.8426 0.8979
## [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 99"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 19 6 0 0
## Medio 5 34 11 3
## Alto 0 0 112 21
## Excelente 0 0 13 117
##
## Overall Statistics
##
## Accuracy : 0.827
## 95% CI : (0.7826, 0.8656)
## No Information Rate : 0.4135
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7392
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.79167 0.85000 0.8235 0.8298
## Specificity 0.98107 0.93688 0.8976 0.9350
## Pos Pred Value 0.76000 0.64151 0.8421 0.9000
## Neg Pred Value 0.98418 0.97917 0.8846 0.8863
## Prevalence 0.07038 0.11730 0.3988 0.4135
## Detection Rate 0.05572 0.09971 0.3284 0.3431
## Detection Prevalence 0.07331 0.15543 0.3900 0.3812
## Balanced Accuracy 0.88637 0.89344 0.8605 0.8824
## [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 100"
## Confusion Matrix and Statistics
##
## Reference
## Prediction Bajo Medio Alto Excelente
## Bajo 24 4 0 0
## Medio 3 35 11 1
## Alto 0 0 115 23
## Excelente 0 0 10 115
##
## Overall Statistics
##
## Accuracy : 0.8475
## 95% CI : (0.8049, 0.884)
## No Information Rate : 0.4076
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.771
##
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: Bajo Class: Medio Class: Alto Class: Excelente
## Sensitivity 0.88889 0.8974 0.8456 0.8273
## Specificity 0.98726 0.9503 0.8878 0.9505
## Pos Pred Value 0.85714 0.7000 0.8333 0.9200
## Neg Pred Value 0.99042 0.9863 0.8966 0.8889
## Prevalence 0.07918 0.1144 0.3988 0.4076
## Detection Rate 0.07038 0.1026 0.3372 0.3372
## Detection Prevalence 0.08211 0.1466 0.4047 0.3666
## Balanced Accuracy 0.93808 0.9239 0.8667 0.8889
## [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] "--------------------------------------------------------------------------------------"print(vv)## [1] 0 0 0 0 0 9 115 0 28 5 0 2 0 0 1 0 0 0 0
## [20] 3 0 0 0 5 17 0 0 0 0 5 0 0 2 0 3 19 5 11
## [39] 0 0 7 0 0 1 0 0 0 2 0 0 0 0 1 0 1 3 1
## [58] 0 0 6 0 4 0 108 0 0 1 0 0 0 0 0 0 0 0 0
## [77] 24 0 0 10 0 5 4 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 9
## 7 A7 2,3-Butanedione 115
## 9 A9 2,3-Pentanedione 28
## 25 A25 Pyrazine, 2,6-dimethyl- 17
## 36 A36 2,6-Diethylpyrazine 19
## 38 A38 Furfural 11
## 64 A64 1H-Pyrrole, 1-(2-furanylmethyl)- 108
## 77 A77 1H-Pyrrole-2-carboxaldehyde, 1-methyl- 24
## 80 A80 4H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl- 10new_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 + A30 + A9, 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-06vif(modelo1)## A7 A64 A30 A9
## 1.478375 1.208231 1.429581 1.115961plot(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) 88.1096911 92.69797837
## A7 8.0937871 28.38816165
## A64 -0.5724027 -0.05661822
## A30 -2.3771362 -1.08699278
## A9 -8.5800537 -0.69756488