code: def test_inverse_transform(self):
      d = {"col1": ["a", "a", "c"], "col2": ["w", "e", "d"]}
      df = pd.DataFrame(data=d)
      lb = LabelBinarizer()
      # check first column
      lb.fit(df, "col1")
      bb = lb.transform(df, "col1")
      self.assertTrue("col1_c" in bb.columns)
      self.assertTrue(np.sum(bb["col1_c"]) == 1)
      bb = lb.inverse_transform(bb)
      self.assertTrue("col1_c" not in bb.columns)
      # check second column
      lb = LabelBinarizer()
      lb.fit(df, "col2")
      bb = lb.transform(df, "col2")
      self.assertTrue("col2_w" in bb.columns)
      self.assertTrue("col2_e" in bb.columns)
      self.assertTrue("col2_d" in bb.columns)
      self.assertTrue(np.sum(bb["col2_w"]) == 1)
      bb = lb.inverse_transform(bb)
      self.assertTrue("col2_w" not in bb.columns)
  
file_path: mljar-supervised/tests/tests_preprocessing/test_label_binarizer.py
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  from supervised.preprocessing.label_binarizer import LabelBinarizer
label_desc: Use image node_id 6 for calling the LabelBinarizerTest obj's underlying member method code with example usage: obj.test_inverse_transform() without return types