parameters: (self, X)
return_statement: return self._predict(X)
docstring: Return predictions for X for each estimator.
  
          Parameters
          ----------
          X : {array-like, sparse matrix}, shape (n_samples, n_features)
              The input samples.
  
          Returns
          -------
          predictions: array of shape (n_samples, n_classifiers)
              Values predicted by each regressor.
docstring_summary: Return predictions for X for each estimator.
docstring_tokens: Return predictions for X for each estimator .
function: def transform(self, X):
          """Return predictions for X for each estimator.
  
          Parameters
          ----------
          X : {array-like, sparse matrix}, shape (n_samples, n_features)
              The input samples.
  
          Returns
          -------
          predictions: array of shape (n_samples, n_classifiers)
              Values predicted by each regressor.
          """
          check_is_fitted(self)
          return self._predict(X)
function_tokens: def transform ( self , X ) : check_is_fitted ( self ) return self . _predict ( X )