main_component_analysis.R

In SMLMS/pguXAI:

library(tidyverse)
library(pguXAI)
library(GGally)

main = function(){
  # load data set and remove class labels
  df_data <- iris %>%
    dplyr::select(-Species)

  # define true class labels
  classes_true <- iris$Species

  # run principle component analysis
  ca <- pguXAI::componentAnalysis.pca$new()
  ca$train(obj=df_data)

  # plot results
  ca$evr_overview_plot()

  ca$evr_detail_plot() %>%
    show()

  ca$cos2_corrplot() %>%
    show()

  ca$cos2_barplot()

  ca$contrib_corrplot() %>%
    show()

  ca$contrib_barplot()

  # ca$df_components %>%
  df_data %>%
    #dplyr::mutate(Dim.5 = Dim.1 * 2) %>%
    GGally::ggpairs(axisLabels = "none") +
    ggplot2::theme_bw() +
    ggplot2::labs(title = "Raw data correlation matrix")

  # fin <- "done"
  # fin
}

main()