parameters: (self, X)
return_statement: return self.best_estimator_.predict(X)
docstring: Call predict on the estimator with the best found parameters.
  
          Only available if ``refit=True`` and the underlying estimator supports
          ``predict``.
  
          Parameters
          ----------
          X : indexable, length n_samples
              Must fulfill the input assumptions of the
              underlying estimator.
docstring_summary: Call predict on the estimator with the best found parameters.
docstring_tokens: Call predict on the estimator with the best found parameters .
function: def predict(self, X):
          """Call predict on the estimator with the best found parameters.
  
          Only available if ``refit=True`` and the underlying estimator supports
          ``predict``.
  
          Parameters
          ----------
          X : indexable, length n_samples
              Must fulfill the input assumptions of the
              underlying estimator.
  
          """
          self._check_is_fitted('predict')
          return self.best_estimator_.predict(X)
function_tokens: def predict ( self , X ) : self . _check_is_fitted ( 'predict' ) return self . best_estimator_ . predict ( X )