class_docstr: A class to test the TED_Cartesian explainer
class_docstr_tok: ["A","class","to","test","the","TED_Cartesian","explainer"]
docstr: Perform setup code of opening datafile, constructing train/test split, created TED_CartesianExplainer and
docstr_tok: ["Perform","setup","code","of","opening","datafile",",","constructing","train\/test","split",",","created","TED_CartesianExplainer","and"]
code: def setUp(self):
      """
      Perform setup code of opening datafile, constructing train/test split, created TED_CartesianExplainer and
      """
  
      # Decompose the dataset into X, Y, E
      X, Y, E = TEDDataset().load_file("Retention.csv")
  
      # set up train/test split
      (
          self.X_train,
          self.X_test,
          self.Y_train,
          self.Y_test,
          self.E_train,
          self.E_test,
      ) = train_test_split(X, Y, E, test_size=0.20, random_state=0)
  
      # Create classifier and pass to TED_Cartesian
      self.estimator = svm.SVC(kernel="linear")
      self.ted = TED_CartesianExplainer(self.estimator)
      self.ted.fit(self.X_train, self.Y_train, self.E_train)
  
file_path: AIX360/tests/ted/test_TED_Cartesian.py
imports: import unittest
  import os
  import pandas
  from sklearn import svm
  from sklearn.model_selection import train_test_split
  from aix360.algorithms.ted import TED_CartesianExplainer
  from aix360.datasets.ted_dataset import TEDDataset
label_desc: Use image node_id 1 for calling the TestTED_Cartesian obj's underlying member method code with example usage: obj.setUp() without return types