class_docstr: Wraps `MultiLabelBinarizer` in a pipeline safe transformer
  
  Args:
      sparse_output (bool): convert output to sparse matrix
class_docstr_tok: ["Wraps","`","MultiLabelBinarizer","`","in","a","pipeline","safe","transformer","Args",":","sparse_output","(","bool",")",":","convert","output","to","sparse","matrix"]
docstr: Fit MultiLabelBinarizer 
docstr_tok: ["Fit","MultiLabelBinarizer"]
code: def fit(self, X, y=None):
      """Fit MultiLabelBinarizer"""
      self.transformer.fit(X)
      return self
  
imports: import warnings
  import pandas
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.preprocessing import MultiLabelBinarizer, FunctionTransformer, LabelEncoder, normalize
  from sklearn.feature_extraction.text import HashingVectorizer
  from sklearn import feature_selection
label_desc: Use image node_id 2 for calling the MultihotEncoder obj's underlying member method code with example usage: obj.fit(X, y) and returns: self