Attractive Confusion Matrices in R Plotted with fourfoldplot

As part of writing analyses using neural networks I thought of displaying a confusion matrix, but went looking for something more. What I found was either ugly and simple, or attractive but complicated. The following code demonstrates using fourfoldplot, with original insight gained from fourfoldplot: A prettier confusion matrix in base R, and a great documentation page, R Documentation's page for fourfoldplot.

The code is below, as is the related graph. Source data can be found here.

 ###############################################  
 # Load and clean data  
 ################################################     

 Politics.df <- read.csv("BigFiveScoresByState.csv", na.strings = c("", "NA"))  
 Politics.df <- na.omit(Politics.df)  
   
 ################################################  
 # Neural Net with nnet and caret  
 ################################################   

 # load packages  
 library(nnet)  
 library(caret)  
   
 # set equation  
 equation <- as.formula("Liberal ~ Openness + Conscientiousness + Extraversion + Neuroticism + Agreeableness")  
   
 # train, predict, combine  
 Politics.model <- train(equation, Politics.df, method = 'nnet', linout = TRUE, trace = FALSE)  
 Politics.model.predicted <- predict(Politics.model, Politics.df)  
 Politics.model.combined <- cbind(Politics.model.predicted, Politics.df)  
   
 ################################################  
 # Plot with FourFoldPlot  
 ################################################    

 # create the confusion matrix
 Politics.model.matrix <- confusionMatrix(Politics.model.combined$predictionBinary, Politics.model.combined$Liberal)  

 # set the column and row names
 colnames(Politics.model.matrix$table) <- c("Conservative", "Liberal")  
 rownames(Politics.model.matrix$table) <- c("Conservative", "Liberal")  

  # generate the plot
 fourfoldplot(Politics.model.matrix$table, color = c("Red", "Green"), conf.level = 0, margin = 1, main = "Confusion Matrix for Model")