code: def generateFeatures(numInstances):
      """generate the features (X) values for the dataset
      Args:
          numInstances (int) : number of instances to genreate
      Returns:
          dataset (list of lists) : the dataset with features, but no labels or explanations yet
      """
      assert numInstances > 0
  
      dataset = []
      for i in range(numInstances):
          instance = []
  
          # POS  ORG    Pot  Rating Slope  SALC  TENL H       BTEN LH
          chooseValueAndAppend(
              instance, Integer4Population, featureThresholds[0][1]
          )  # Position
          chooseValueAndAppend(
              instance, Integer3Population, featureThresholds[1][1]
          )  # Org
          chooseValueAndAppend(
              instance, YesNoPopulation, featureThresholds[2][1]
          )  # Potential
          chooseValueAndAppend(
              instance, HighMedLowPopulation, featureThresholds[3][1]
          )  # Rating
          chooseValueAndAppend(
              instance, HighMedLowPopulation, featureThresholds[4][1]
          )  # Rating slope
          chooseValueAndAppend(
              instance, HighMedLowPopulation, featureThresholds[5][1]
          )  # Sal competitiveness
  
          val1 = chooseRangeValue(
              featureThresholds[6][1], featureThresholds[6][2]
          )  # Tenure
          instance.append(val1)
  
          # Position tenure needs to be <= Tenure
          val2 = chooseRangeValue(
              featureThresholds[7][1], featureThresholds[7][2]
          )  # Pos Tenure
          if val2 > val1:
              val2 = val1
          instance.append(val2)
          dataset.append(instance)
  
      return dataset
  
file_path: AIX360/aix360/data/ted_data/GenerateData.py
imports: import random
  from random import choices
  import pandas
label_desc: Use image node_id 8 for calling a global function with example usage: generateFeatures(numInstances) and returns: dataset