def __init__(self, estimator, param_grid, sc=None, partitions='auto', preds=False, scoring=None, n_jobs=None, iid='warn', refit=True, cv=5, verbose=0, pre_dispatch='2*n_jobs', error_score='raise-deprecating', return_train_score=False): GridSearchCV.__init__(self, estimator, param_grid, scoring=scoring, n_jobs=n_jobs, iid=iid, refit=refit, cv=cv, verbose=verbose, pre_dispatch=pre_dispatch, error_score=error_score, return_train_score=return_train_score) self.sc = sc self.partitions = partitions self.preds = preds
def __init__(self, gs_params): """ Args: gs_params (dict) search parameters for hyperparameter optimization. """ # constructs pipline steps scale = StandardScaler() regressor = RandomForestRegressor() pipe = Pipeline(steps=[('scale', scale), ('regressor', regressor)]) # constructs the gridsearch estimator GridSearchCV.__init__(pipe, gs_params, refit=True, cv=5, scoring='r2')