class_docstr: Base class for PCA methods.
  
  Warning: This class should not be used directly.
  Use derived classes instead.
docstr: Placeholder for fit. Subclasses should implement this method!
  
  Fit the model with X.
  
  Parameters
  ----------
  X : array-like, shape (n_samples, n_features)
      Training data, where n_samples is the number of samples and
      n_features is the number of features.
  
  Returns
  -------
  self : object
      Returns the instance itself.
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code: def fit(X, y=None, session=None, run_kwargs=None):
      """Placeholder for fit. Subclasses should implement this method!
  
      Fit the model with X.
  
      Parameters
      ----------
      X : array-like, shape (n_samples, n_features)
          Training data, where n_samples is the number of samples and
          n_features is the number of features.
  
      Returns
      -------
      self : object
          Returns the instance itself.
      """
  
file_path: mars/mars/learn/decomposition/_base.py
imports: from abc import ABCMeta, abstractmethod
  from sklearn.base import BaseEstimator, TransformerMixin
  from ...None import tensor
  from ...tensor import linalg
  from ..utils import check_array
  from ..utils.validation import check_is_fitted
label_desc: Use image node_id 3 for calling the _BasePCA obj's underlying member method code with example usage: obj.fit(X, y, session, run_kwargs) without return types