class_docstr: Test behaviour of classification_report
docstr: Classification report should ignore any columns that are no needed by predict
docstr_tok: ["Classification","report","should","ignore","any","columns","that","are","no","needed","by","predict"]
code: def test_report_ignores_unrequired_columns_in_data(
      self, train_data_idx, train_data_discrete, test_data_c_discrete
  ):
      """Classification report should ignore any columns that are no needed by predict"""
  
      bn = BayesianNetwork(
          from_pandas(train_data_idx, w_threshold=0.3)
      ).fit_node_states(train_data_discrete)
      train_data_discrete["NEW_COL"] = [1] * len(train_data_discrete)
      bn.fit_cpds(train_data_discrete)
      classification_report(bn, test_data_c_discrete, "c")
  
imports: import math
  import random
  import numpy
  import pandas
  from causalnex.evaluation import classification_report, roc_auc
  from causalnex.network import BayesianNetwork
  from causalnex.structure.notears import from_pandas
  from causalnex.structure.structuremodel import StructureModel
label_desc: Use image node_id 2 for calling the TestClassificationReport obj's underlying member method code with example usage: obj.test_report_ignores_unrequired_columns_in_data(train_data_idx, train_data_discrete, test_data_c_discrete) without return types