Function to reproduce the KS Chart in machinelearningplus.com/evaluation-metrics-classification-models

kolmogorov_smirnov_chart.R

library(InformationValue)
library(ggplot2)
ks_plot <- function (actuals, predictedScores) {
    rank <- 0:10
    ks_table_out <- InformationValue:::ks_table(actuals = actuals, predictedScores = predictedScores)
    perc_positive <- c(0, ks_table_out$cum_perc_responders) * 100
    perc_negative <- c(0, ks_table_out$cum_perc_non_responders) * 100
    random_prediction <- seq(0, 100, 10)
    df <- data.frame(rank, random_prediction, perc_positive, perc_negative)
    df_stack <- stack(df, c(random_prediction, perc_positive, perc_negative))
    df_stack$rank <- rep(rank, 3)
    df_stack$delta <- df_stack$values[12:22] - df_stack$values[1:11]
    values <- df_stack$values
    ind <- df_stack$ind
    
    rowmax <- which.max(ks_table_out$difference)
    l_start <- ks_table_out[rowmax, "cum_perc_non_responders"]
    l_end <- ks_table_out[rowmax, "cum_perc_responders"]
    
    print(ggplot2::ggplot(df_stack, aes(x = rank, y = values, 
        colour = ind, label = paste0(round(values, 2), "%"))) + 
        geom_line(size = 1.25) + 
          labs(x = "rank", y = "Percentage +Ve & -Ve Captured", 
        title = "KS Chart", subtitle=paste("KS Statistic: ", ks_stat(actuals, predictedScores))) + 
          theme(plot.title = element_text(size = 20, 
        face = "bold")) + 
          geom_text(aes(y = values + 4)) + 
          scale_x_continuous(breaks=0:10, labels=0:10) + 
      geom_segment(x = rowmax, y = l_start*100, xend = rowmax, yend = l_end*100, col="red", arrow = arrow(length = unit(0.05, "npc"), ends="both"), linetype = "dashed", lwd=1))
}

Where does ks_table() function come from?