class_docstr: Base class for all pipeline objects.
  
  Notes
  -----
  This class should not be instantiated, only subclassed.
docstr: Fit the selected algorithm to the training data.
  
  Parameters
  ----------
  X : array-like or sparse, shape = (n_samples, n_features)
      Training data. The preferred type of the matrix (dense or sparse)
      depends on the estimator selected.
  
  y : array-like
      Targets
  
  fit_params : dict
      See the documentation of sklearn.pipeline.Pipeline for formatting
      instructions.
  
  Returns
  -------
  self : returns an instance of self.
  
  Raises
  ------
  NoModelException
      NoModelException is raised if fit() is called without specifying
      a classification algorithm first.
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code: def fit(self, X, y, **fit_params):
      """Fit the selected algorithm to the training data.
  
      Parameters
      ----------
      X : array-like or sparse, shape = (n_samples, n_features)
          Training data. The preferred type of the matrix (dense or sparse)
          depends on the estimator selected.
  
      y : array-like
          Targets
  
      fit_params : dict
          See the documentation of sklearn.pipeline.Pipeline for formatting
          instructions.
  
      Returns
      -------
      self : returns an instance of self.
  
      Raises
      ------
      NoModelException
          NoModelException is raised if fit() is called without specifying
          a classification algorithm first.
      """
      X, fit_params = self.fit_transformer(X, y, **fit_params)
      self.fit_estimator(X, y, **fit_params)
      return self
  
imports: from abc import ABCMeta
  from typing import Dict, Optional, Union
  import numpy
  import scipy.sparse
  from ConfigSpace import Configuration
  from sklearn.pipeline import Pipeline
  import autosklearn.pipeline.create_searchspace_util
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from .components.base import AutoSklearnChoice, AutoSklearnComponent
label_desc: Use image node_id 2 for calling the BasePipeline obj's underlying member method code with example usage: obj.fit(X, y) and returns: self