parameters: (self, X)
return_statement: return self.base_estimator_.predict(X)
docstring: Perform classification on an array of test vectors X.
  
          Parameters
          ----------
          X : array-like, shape = (n_samples, n_features)
  
          Returns
          -------
          C : array, shape = (n_samples,)
              Predicted target values for X, values are from ``classes_``
docstring_summary: Perform classification on an array of test vectors X.
docstring_tokens: Perform classification on an array of test vectors X .
function: def predict(self, X):
          """Perform classification on an array of test vectors X.
  
          Parameters
          ----------
          X : array-like, shape = (n_samples, n_features)
  
          Returns
          -------
          C : array, shape = (n_samples,)
              Predicted target values for X, values are from ``classes_``
          """
          check_is_fitted(self, ["classes_", "n_classes_"])
          X = check_array(X)
          return self.base_estimator_.predict(X)
function_tokens: def predict ( self , X ) : check_is_fitted ( self , [ "classes_" , "n_classes_" ] ) X = check_array ( X ) return self . base_estimator_ . predict ( X )