class_docstr: Mixin class for all transformers in scikit-learn.
docstr: Fit to data, then transform it.
  Fits transformer to X and y with optional parameters fit_params
  and returns a transformed version of X.
  Parameters
  ----------
  X : numpy array of shape [n_samples, n_features]
      Training set.
  y : numpy array of shape [n_samples]
      Target values.
  Returns
  -------
  X_new : numpy array of shape [n_samples, n_features_new]
      Transformed array.
docstr_tok: ["Fit","to","data",",","then","transform","it",".","Fits","transformer","to","X","and","y","with","optional","parameters","fit_params","and","returns","a","transformed","version","of","X.","Parameters","--","--","--","--","--","X",":","numpy","array","of","shape","[","n_samples",",","n_features","]","Training","set",".","y",":","numpy","array","of","shape","[","n_samples","]","Target","values",".","Returns","--","--","--","-","X_new",":","numpy","array","of","shape","[","n_samples",",","n_features_new","]","Transformed","array","."]
code: def fit_transform(self, X, y=None, **fit_params):
      """Fit to data, then transform it.
      Fits transformer to X and y with optional parameters fit_params
      and returns a transformed version of X.
      Parameters
      ----------
      X : numpy array of shape [n_samples, n_features]
          Training set.
      y : numpy array of shape [n_samples]
          Target values.
      Returns
      -------
      X_new : numpy array of shape [n_samples, n_features_new]
          Transformed array.
      """
      # non-optimized default implementation; override when a better
      # method is possible for a given clustering algorithm
      if y is None:
          # fit method of arity 1 (unsupervised transformation)
          return self.fit(X, **fit_params).transform(X)
      else:
          # fit method of arity 2 (supervised transformation)
          return self.fit(X, y, **fit_params).transform(X)
  
imports: import copy
  import warnings
  from collections import defaultdict
  import numpy
  from scipy import sparse
  from ..None import six
  from ..funcsigs import signature
label_desc: Use image node_id 1 for calling the TransformerMixin obj's underlying member method code with example usage: obj.fit_transform(X, y) and returns: self, self