rm(list=ls())
for(model in c(paste0("model",c(6:33,35,36)))){
print(model)
pred <- read.csv(paste0("C:/Users/gerhard/Documents/hpc-mini/chamber_gain_corrected/",model,"_results.csv"),header=F)
act <- read.csv(paste0("C:/Users/gerhard/Documents/hpc-mini/chamber_gain_corrected/model24_y_test.csv"),header=F)
names(pred) <- "pred"
names(act) <- "act"
pred_act <- data.frame(cbind(pred,act))
six_tracklet_pred <- c()
for(i in seq(1,nrow(pred),6)){
j=i+5
this.dat <- prod(pred[i:j,])/sum(prod(pred[i:j,]),prod(1-pred[i:j,]))
six_tracklet_pred <- c(six_tracklet_pred,this.dat)
}
six_tracklet_pred <- data.frame(six_tracklet_pred)
six_tracklet_pred <- na.omit(six_tracklet_pred)
six_tracklet_real <- c()
for(i in seq(1,nrow(act),6)){
this.dat <- act[i,]
six_tracklet_real <- c(six_tracklet_real,this.dat)
}
six_tracklet_real <- data.frame(six_tracklet_real)
which(is.na(six_tracklet_real))
pred_act <- data.frame(cbind(six_tracklet_pred,six_tracklet_real))
elec_pi_eff_func <- function(model_1.preds,model_1.labels){
# model_1.preds <- read.csv(model_1.preds,header=F, sep="")
#
# model_1.labels <- read.csv(model_1.labels,header=F, sep="")
model_1 <- data.frame(cbind(model_1.preds,model_1.labels))
model_1.electrons <- which(model_1[,2]==1)
electrons <- model_1[model_1.electrons,]
pions <- model_1[-as.numeric(model_1.electrons),]
electrons <- data.frame(electrons)
names(electrons) <- c("prediction","label")
pions <- data.frame(pions)
names(pions) <- c("prediction","label")
electron_efficiency <- function(electrons.,par){
electrons <- electrons.
electrons$electron_pred <- ifelse(electrons$prediction>=par[1],1,0)
correct <- ifelse(electrons$electron_pred==electrons$label,1,0)
error_metric <- sum(correct)/nrow(electrons)
error_metric <- (error_metric-0.9)^2
return(error_metric)
}
res <- optim(par=c(0),fn=electron_efficiency,lower = 0,upper = 1,electrons.=electrons,method="Brent")
require(ggplot2)
g <- ggplot(pred_act,aes(pred_act[,1],colour=factor(pred_act[,2])))+geom_histogram(bins = 1000)+facet_wrap(factor(pred_act[,2]))
print(g)
hist(pred_act[,1],breaks=1000)
abline(v=res$par,col="red")
electrons$predicted_label <- ifelse(electrons$prediction>=res$par,1,0)
print(paste0("Electron Efficiency: ",sum(electrons$predicted_label)/nrow(electrons)))
pions$predicted_label <- ifelse(pions$prediction>=res$par,1,0)
pions$misclassified_as_electron <- ifelse(pions$predicted_label==1,1,0)
print(paste0("Pion Efficiency: ",sum(pions$misclassified_as_electron)/nrow(pions)))
pred_act$final_pred <- ifelse(pred_act[,1]>=res$par,1,0)
require(caret)
print(caret::confusionMatrix(data=factor(pred_act$final_pred),reference = factor(pred_act[,2])))
}
elec_pi_eff_func(pred_act[,1],pred_act[,2])
}
## [1] "model6"
## Loading required package: ggplot2
## Registered S3 methods overwritten by 'ggplot2':
## method from
## [.quosures rlang
## c.quosures rlang
## print.quosures rlang
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.255432227468776"
## Loading required package: caret
## Loading required package: lattice
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 36425 4892
## 1 12496 44029
##
## Accuracy : 0.8223
## 95% CI : (0.8199, 0.8247)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6446
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.7446
## Specificity : 0.9000
## Pos Pred Value : 0.8816
## Neg Pred Value : 0.7789
## Prevalence : 0.5000
## Detection Rate : 0.3723
## Detection Prevalence : 0.4223
## Balanced Accuracy : 0.8223
##
## 'Positive' Class : 0
##
## [1] "model7"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.157744118067905"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 41204 4892
## 1 7717 44029
##
## Accuracy : 0.8711
## 95% CI : (0.869, 0.8732)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7423
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.8423
## Specificity : 0.9000
## Pos Pred Value : 0.8939
## Neg Pred Value : 0.8509
## Prevalence : 0.5000
## Detection Rate : 0.4211
## Detection Prevalence : 0.4711
## Balanced Accuracy : 0.8711
##
## 'Positive' Class : 0
##
## [1] "model8"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.16375380715848"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 40910 4892
## 1 8011 44029
##
## Accuracy : 0.8681
## 95% CI : (0.866, 0.8702)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7362
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.8362
## Specificity : 0.9000
## Pos Pred Value : 0.8932
## Neg Pred Value : 0.8461
## Prevalence : 0.5000
## Detection Rate : 0.4181
## Detection Prevalence : 0.4681
## Balanced Accuracy : 0.8681
##
## 'Positive' Class : 0
##
## [1] "model9"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.133541832750761"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 42388 4892
## 1 6533 44029
##
## Accuracy : 0.8832
## 95% CI : (0.8812, 0.8852)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7665
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.8665
## Specificity : 0.9000
## Pos Pred Value : 0.8965
## Neg Pred Value : 0.8708
## Prevalence : 0.5000
## Detection Rate : 0.4332
## Detection Prevalence : 0.4832
## Balanced Accuracy : 0.8832
##
## 'Positive' Class : 0
##
## [1] "model10"
## [1] "Electron Efficiency: 0.899940720753868"
## [1] "Pion Efficiency: 0.112323950859549"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 43426 4895
## 1 5495 44026
##
## Accuracy : 0.8938
## 95% CI : (0.8919, 0.8957)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7876
##
## Mcnemar's Test P-Value : 4.19e-09
##
## Sensitivity : 0.8877
## Specificity : 0.8999
## Pos Pred Value : 0.8987
## Neg Pred Value : 0.8890
## Prevalence : 0.5000
## Detection Rate : 0.4438
## Detection Prevalence : 0.4939
## Balanced Accuracy : 0.8938
##
## 'Positive' Class : 0
##
## [1] "model11"
## [1] "Electron Efficiency: 0.900083808589358"
## [1] "Pion Efficiency: 0.0856074078616545"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 44733 4888
## 1 4188 44033
##
## Accuracy : 0.9072
## 95% CI : (0.9054, 0.909)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8145
##
## Mcnemar's Test P-Value : 2.181e-13
##
## Sensitivity : 0.9144
## Specificity : 0.9001
## Pos Pred Value : 0.9015
## Neg Pred Value : 0.9131
## Prevalence : 0.5000
## Detection Rate : 0.4572
## Detection Prevalence : 0.5072
## Balanced Accuracy : 0.9072
##
## 'Positive' Class : 0
##
## [1] "model12"
## [1] "Electron Efficiency: 0.899818074037734"
## [1] "Pion Efficiency: 0.41783692074978"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 28480 4901
## 1 20441 44020
##
## Accuracy : 0.741
## 95% CI : (0.7382, 0.7437)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.482
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5822
## Specificity : 0.8998
## Pos Pred Value : 0.8532
## Neg Pred Value : 0.6829
## Prevalence : 0.5000
## Detection Rate : 0.2911
## Detection Prevalence : 0.3412
## Balanced Accuracy : 0.7410
##
## 'Positive' Class : 0
##
## [1] "model13"
## [1] "Electron Efficiency: 0.899940720753868"
## [1] "Pion Efficiency: 0.100345454917111"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 44012 4895
## 1 4909 44026
##
## Accuracy : 0.8998
## 95% CI : (0.8979, 0.9017)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : <2e-16
##
## Kappa : 0.7996
##
## Mcnemar's Test P-Value : 0.8955
##
## Sensitivity : 0.8997
## Specificity : 0.8999
## Pos Pred Value : 0.8999
## Neg Pred Value : 0.8997
## Prevalence : 0.5000
## Detection Rate : 0.4498
## Detection Prevalence : 0.4999
## Balanced Accuracy : 0.8998
##
## 'Positive' Class : 0
##
## [1] "model14"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.488501870362421"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 25023 4892
## 1 23898 44029
##
## Accuracy : 0.7058
## 95% CI : (0.7029, 0.7086)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.4115
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5115
## Specificity : 0.9000
## Pos Pred Value : 0.8365
## Neg Pred Value : 0.6482
## Prevalence : 0.5000
## Detection Rate : 0.2557
## Detection Prevalence : 0.3057
## Balanced Accuracy : 0.7058
##
## 'Positive' Class : 0
##
## [1] "model15"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.474111322336011"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 25727 4892
## 1 23194 44029
##
## Accuracy : 0.7129
## 95% CI : (0.7101, 0.7158)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.4259
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5259
## Specificity : 0.9000
## Pos Pred Value : 0.8402
## Neg Pred Value : 0.6550
## Prevalence : 0.5000
## Detection Rate : 0.2629
## Detection Prevalence : 0.3129
## Balanced Accuracy : 0.7129
##
## 'Positive' Class : 0
##
## [1] "model16"
## [1] "Electron Efficiency: 0.89998160299258"
## [1] "Pion Efficiency: 0.462991353406513"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 26271 4893
## 1 22650 44028
##
## Accuracy : 0.7185
## 95% CI : (0.7157, 0.7213)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.437
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5370
## Specificity : 0.9000
## Pos Pred Value : 0.8430
## Neg Pred Value : 0.6603
## Prevalence : 0.5000
## Detection Rate : 0.2685
## Detection Prevalence : 0.3185
## Balanced Accuracy : 0.7185
##
## 'Positive' Class : 0
##
## [1] "model17"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.473804705545676"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 25742 4892
## 1 23179 44029
##
## Accuracy : 0.7131
## 95% CI : (0.7103, 0.7159)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.4262
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5262
## Specificity : 0.9000
## Pos Pred Value : 0.8403
## Neg Pred Value : 0.6551
## Prevalence : 0.5000
## Detection Rate : 0.2631
## Detection Prevalence : 0.3131
## Balanced Accuracy : 0.7131
##
## 'Positive' Class : 0
##
## [1] "model18"
## [1] "Electron Efficiency: 0.899961161873224"
## [1] "Pion Efficiency: 0.44220273502177"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 27288 4894
## 1 21633 44027
##
## Accuracy : 0.7289
## 95% CI : (0.7261, 0.7317)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.4578
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5578
## Specificity : 0.9000
## Pos Pred Value : 0.8479
## Neg Pred Value : 0.6705
## Prevalence : 0.5000
## Detection Rate : 0.2789
## Detection Prevalence : 0.3289
## Balanced Accuracy : 0.7289
##
## 'Positive' Class : 0
##
## [1] "model19"
## [1] "Electron Efficiency: 0.89998160299258"
## [1] "Pion Efficiency: 0.319085873142413"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 33311 4893
## 1 15610 44028
##
## Accuracy : 0.7904
## 95% CI : (0.7879, 0.793)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.5809
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.6809
## Specificity : 0.9000
## Pos Pred Value : 0.8719
## Neg Pred Value : 0.7383
## Prevalence : 0.5000
## Detection Rate : 0.3405
## Detection Prevalence : 0.3905
## Balanced Accuracy : 0.7904
##
## 'Positive' Class : 0
##
## [1] "model20"
## [1] "Electron Efficiency: 0.900022485231291"
## [1] "Pion Efficiency: 0.400461969297439"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 29330 4891
## 1 19591 44030
##
## Accuracy : 0.7498
## 95% CI : (0.7471, 0.7525)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.4996
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.5995
## Specificity : 0.9000
## Pos Pred Value : 0.8571
## Neg Pred Value : 0.6921
## Prevalence : 0.5000
## Detection Rate : 0.2998
## Detection Prevalence : 0.3498
## Balanced Accuracy : 0.7498
##
## 'Positive' Class : 0
##
## [1] "model21"
## [1] "Electron Efficiency: 0.900063367470003"
## [1] "Pion Efficiency: 0.086915639500419"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 44669 4889
## 1 4252 44032
##
## Accuracy : 0.9066
## 95% CI : (0.9047, 0.9084)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8131
##
## Mcnemar's Test P-Value : 2.889e-11
##
## Sensitivity : 0.9131
## Specificity : 0.9001
## Pos Pred Value : 0.9013
## Neg Pred Value : 0.9119
## Prevalence : 0.5000
## Detection Rate : 0.4565
## Detection Prevalence : 0.5065
## Balanced Accuracy : 0.9066
##
## 'Positive' Class : 0
##
## [1] "model22"
## [1] "Electron Efficiency: 0.900063367470003"
## [1] "Pion Efficiency: 0.057071605241103"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 46129 4889
## 1 2792 44032
##
## Accuracy : 0.9215
## 95% CI : (0.9198, 0.9232)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.843
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9429
## Specificity : 0.9001
## Pos Pred Value : 0.9042
## Neg Pred Value : 0.9404
## Prevalence : 0.5000
## Detection Rate : 0.4715
## Detection Prevalence : 0.5214
## Balanced Accuracy : 0.9215
##
## 'Positive' Class : 0
##
## [1] "model23"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.0645530549252877"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 45763 4892
## 1 3158 44029
##
## Accuracy : 0.9177
## 95% CI : (0.916, 0.9194)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8354
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9354
## Specificity : 0.9000
## Pos Pred Value : 0.9034
## Neg Pred Value : 0.9331
## Prevalence : 0.5000
## Detection Rate : 0.4677
## Detection Prevalence : 0.5177
## Balanced Accuracy : 0.9177
##
## 'Positive' Class : 0
##
## [1] "model24"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.241143885039145"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 37124 4892
## 1 11797 44029
##
## Accuracy : 0.8294
## 95% CI : (0.8271, 0.8318)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.6589
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.7589
## Specificity : 0.9000
## Pos Pred Value : 0.8836
## Neg Pred Value : 0.7887
## Prevalence : 0.5000
## Detection Rate : 0.3794
## Detection Prevalence : 0.4294
## Balanced Accuracy : 0.8294
##
## 'Positive' Class : 0
##
## [1] "model25"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.0451135504180209"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 46714 4892
## 1 2207 44029
##
## Accuracy : 0.9274
## 95% CI : (0.9258, 0.9291)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8549
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9549
## Specificity : 0.9000
## Pos Pred Value : 0.9052
## Neg Pred Value : 0.9523
## Prevalence : 0.5000
## Detection Rate : 0.4774
## Detection Prevalence : 0.5274
## Balanced Accuracy : 0.9274
##
## 'Positive' Class : 0
##
## [1] "model26"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.0454814905664234"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 46696 4892
## 1 2225 44029
##
## Accuracy : 0.9273
## 95% CI : (0.9256, 0.9289)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8545
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9545
## Specificity : 0.9000
## Pos Pred Value : 0.9052
## Neg Pred Value : 0.9519
## Prevalence : 0.5000
## Detection Rate : 0.4773
## Detection Prevalence : 0.5273
## Balanced Accuracy : 0.9273
##
## 'Positive' Class : 0
##
## [1] "model27"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.172707017436275"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 40472 4892
## 1 8449 44029
##
## Accuracy : 0.8636
## 95% CI : (0.8615, 0.8658)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7273
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.8273
## Specificity : 0.9000
## Pos Pred Value : 0.8922
## Neg Pred Value : 0.8390
## Prevalence : 0.5000
## Detection Rate : 0.4136
## Detection Prevalence : 0.4636
## Balanced Accuracy : 0.8636
##
## 'Positive' Class : 0
##
## [1] "model28"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.0583185135218005"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 46068 4892
## 1 2853 44029
##
## Accuracy : 0.9208
## 95% CI : (0.9191, 0.9225)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8417
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9417
## Specificity : 0.9000
## Pos Pred Value : 0.9040
## Neg Pred Value : 0.9391
## Prevalence : 0.5000
## Detection Rate : 0.4708
## Detection Prevalence : 0.5208
## Balanced Accuracy : 0.9208
##
## 'Positive' Class : 0
##
## [1] "model29"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.0592179227734511"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 46024 4892
## 1 2897 44029
##
## Accuracy : 0.9204
## 95% CI : (0.9187, 0.9221)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8408
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9408
## Specificity : 0.9000
## Pos Pred Value : 0.9039
## Neg Pred Value : 0.9383
## Prevalence : 0.5000
## Detection Rate : 0.4704
## Detection Prevalence : 0.5204
## Balanced Accuracy : 0.9204
##
## 'Positive' Class : 0
##
## [1] "model30"
## [1] "Electron Efficiency: 0.900022485231291"
## [1] "Pion Efficiency: 0.0530855869667423"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 46324 4891
## 1 2597 44030
##
## Accuracy : 0.9235
## 95% CI : (0.9218, 0.9251)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8469
##
## Mcnemar's Test P-Value : < 2.2e-16
##
## Sensitivity : 0.9469
## Specificity : 0.9000
## Pos Pred Value : 0.9045
## Neg Pred Value : 0.9443
## Prevalence : 0.5000
## Detection Rate : 0.4735
## Detection Prevalence : 0.5234
## Balanced Accuracy : 0.9235
##
## 'Positive' Class : 0
##
## [1] "model31"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.105578381472169"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 43756 4892
## 1 5165 44029
##
## Accuracy : 0.8972
## 95% CI : (0.8953, 0.8991)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.7944
##
## Mcnemar's Test P-Value : 0.006682
##
## Sensitivity : 0.8944
## Specificity : 0.9000
## Pos Pred Value : 0.8994
## Neg Pred Value : 0.8950
## Prevalence : 0.5000
## Detection Rate : 0.4472
## Detection Prevalence : 0.4972
## Balanced Accuracy : 0.8972
##
## 'Positive' Class : 0
##
## [1] "model32"
## [1] "Electron Efficiency: 0.899940720753868"
## [1] "Pion Efficiency: 0.104965147891499"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 43786 4895
## 1 5135 44026
##
## Accuracy : 0.8975
## 95% CI : (0.8956, 0.8994)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2e-16
##
## Kappa : 0.795
##
## Mcnemar's Test P-Value : 0.01701
##
## Sensitivity : 0.8950
## Specificity : 0.8999
## Pos Pred Value : 0.8994
## Neg Pred Value : 0.8955
## Prevalence : 0.5000
## Detection Rate : 0.4475
## Detection Prevalence : 0.4975
## Balanced Accuracy : 0.8975
##
## 'Positive' Class : 0
##
## [1] "model33"
## [1] "Electron Efficiency: 0.900002044111936"
## [1] "Pion Efficiency: 0.0855869667422988"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 44734 4892
## 1 4187 44029
##
## Accuracy : 0.9072
## 95% CI : (0.9054, 0.909)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8144
##
## Mcnemar's Test P-Value : 1.485e-13
##
## Sensitivity : 0.9144
## Specificity : 0.9000
## Pos Pred Value : 0.9014
## Neg Pred Value : 0.9132
## Prevalence : 0.5000
## Detection Rate : 0.4572
## Detection Prevalence : 0.5072
## Balanced Accuracy : 0.9072
##
## 'Positive' Class : 0
##
## [1] "model35"
## [1] "Electron Efficiency: 0.900042926350647"
## [1] "Pion Efficiency: 0.0892254859876127"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 44556 4890
## 1 4365 44031
##
## Accuracy : 0.9054
## 95% CI : (0.9036, 0.9072)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.8108
##
## Mcnemar's Test P-Value : 5.128e-08
##
## Sensitivity : 0.9108
## Specificity : 0.9000
## Pos Pred Value : 0.9011
## Neg Pred Value : 0.9098
## Prevalence : 0.5000
## Detection Rate : 0.4554
## Detection Prevalence : 0.5054
## Balanced Accuracy : 0.9054
##
## 'Positive' Class : 0
##
## [1] "model36"
## [1] "Electron Efficiency: 0.899961161873224"
## [1] "Pion Efficiency: 0.096461642239529"
## Confusion Matrix and Statistics
##
## Reference
## Prediction 0 1
## 0 44202 4894
## 1 4719 44027
##
## Accuracy : 0.9017
## 95% CI : (0.8999, 0.9036)
## No Information Rate : 0.5
## P-Value [Acc > NIR] : < 2e-16
##
## Kappa : 0.8035
##
## Mcnemar's Test P-Value : 0.07595
##
## Sensitivity : 0.9035
## Specificity : 0.9000
## Pos Pred Value : 0.9003
## Neg Pred Value : 0.9032
## Prevalence : 0.5000
## Detection Rate : 0.4518
## Detection Prevalence : 0.5018
## Balanced Accuracy : 0.9017
##
## 'Positive' Class : 0
##