preds <- read.csv('C:/Users/gerhard/Documents/msc-hpc/round3/feedforward/local/round3_model1_results.csv',
                  header=F,sep="")

actuals <- read.csv('C:/Users/gerhard/Documents/msc-hpc/round3/feedforward/local/round3_model1_y_test.csv',
                    header=F,sep="")

pred_act <- data.frame(
  cbind(
    preds[,2], actuals[,2]
  )
)

hist(pred_act$X1,breaks=1000,freq = F,main="Normalized histogram of stage 1 neural network",xlab="Electron probability")
lines(density(pred_act$X1),col="red",lwd=3)

require(ggplot2)

## Loading required package: ggplot2

## Registered S3 methods overwritten by 'ggplot2':
##   method         from 
##   [.quosures     rlang
##   c.quosures     rlang
##   print.quosures rlang

ggplot(pred_act,aes(X1,fill=factor(X2)))+geom_histogram(bins=100)+facet_wrap(~X2)

simple_roc <- function(labels, scores){
  labels <- labels[order(scores, decreasing=TRUE)]
  data.frame(TPR=cumsum(labels)/sum(labels), FPR=cumsum(!labels)/sum(!labels), labels)
}

ROC <- simple_roc(labels = pred_act$X2,scores = pred_act$X1)

require(pROC)

## Loading required package: pROC

## Type 'citation("pROC")' for a citation.

## 
## Attaching package: 'pROC'

## The following objects are masked from 'package:stats':
## 
##     cov, smooth, var

ggplot(ROC,aes(x=FPR,y=TPR))+geom_line()+ ggtitle(paste0("Area Under ROC Curve: ",auc(pred_act$X2,ifelse(pred_act$X1>0.5,1,0))))

preds <- read.csv('C:/Users/gerhard/Documents/msc-hpc/round3/feedforward/local/round3_model2_results.csv',
                  header=F,sep="")

actuals <- read.csv('C:/Users/gerhard/Documents/msc-hpc/round3/feedforward/local/round3_model2_y_test.csv',
                    header=F,sep="")

pred_act <- data.frame(
  cbind(
    preds[,2], actuals[,2]
  )
)

hist(pred_act$X1,breaks=1000,freq = F,main="Normalized histogram of stage 2 neural network",xlab="Electron probability")
lines(density(pred_act$X1),col="red",lwd=3)

require(ggplot2)

ggplot(pred_act,aes(X1,fill=factor(X2)))+geom_histogram(bins=100)+facet_wrap(~X2)

ROC <- simple_roc(labels = pred_act$X2,scores = pred_act$X1)

ggplot(ROC,aes(x=FPR,y=TPR))+geom_line() + ggtitle(paste0("Area Under ROC Curve: ",auc(pred_act$X2,ifelse(pred_act$X1>0.5,1,0))))

preds <- read.csv('C:/Users/gerhard/Documents/msc-hpc/round3/feedforward/local/round3_model3_results.csv',
                  header=F,sep="")

actuals <- read.csv('C:/Users/gerhard/Documents/msc-hpc/round3/feedforward/local/round3_model3_y_test.csv',
                    header=F,sep="")

pred_act <- data.frame(
  cbind(
    preds[,2], actuals[,2]
  )
)

hist(pred_act$X1,breaks=1000,freq = F,main="Normalized histogram of stage 3 neural network",xlab="Electron probability")
lines(density(pred_act$X1),col="red",lwd=3)

require(ggplot2)

ggplot(pred_act,aes(X1,fill=factor(X2)))+geom_histogram(bins=100)+facet_wrap(~X2)

ROC <- simple_roc(labels = pred_act$X2,scores = pred_act$X1)

ggplot(ROC,aes(x=FPR,y=TPR))+geom_line()+ ggtitle(paste0("Area Under ROC Curve: ",auc(pred_act$X2,ifelse(pred_act$X1>0.5,1,0))))