example_spbfs.R

In IBM/spbfs: Sub-population-based feature selection

install.packages("devtools"); library(devtools)
install_github("IBM/spbfs"); library('spbfs')

#Pre-requirment libraries

#Importing an example database, "The Pima Indians Diabetes". Specifying an initial set of features and an outcome.
{
  library(mlbench)
  data(PimaIndiansDiabetes)
  DATA_FRAME <- PimaIndiansDiabetes
  FEATURE_NAMES = c('pregnant', 'glucose', 'pressure', 'triceps', 'insulin', 'mass', 'pedigree', 'age')
  OUTCOME_VAR_NAME = 'diabetes'
  DATA_FRAME$diabetes<-ifelse(DATA_FRAME$diabetes == "pos", 1, 0) #Converting string labels to binary (1, 0).
}

#Applying sub-population-based feature selection.
{
  Results <- spbfs::get_selected_features(DATA_FRAME = DATA_FRAME,
			                   FEATURE_NAMES = FEATURE_NAMES,
			                   OUTCOME_VAR_NAME = OUTCOME_VAR_NAME,
			                   NUM_ITERATIONS = 100,
			                   NUM_RANDOM_VARIABLES_FOR_MATCHING = 3,
			                   FINAL_SELECTION_THRESHOLD = 0.0,
			                   CALIPER_VALUE = 0.1,
			                   M_value = 1,
			                   P_value_threshold = 0.001,
			                   VERBOSE = 0)
}

#Plotting results.
{
  Results_for_plot <- Results[order(Results$Frequency),]
  barplot(Results_for_plot$Frequency,
          horiz = TRUE,
          names.arg = Results_for_plot$Feature_Name,
          las = 1, cex.names = 0.7, cex.axis = 0.7, xlim = c(0, 1),
          xlab = 'Importance')
}