Module Expr Str Import alias identifier Import alias identifier ImportFrom alias ImportFrom alias ImportFrom alias ImportFrom alias ImportFrom alias identifier ImportFrom alias ImportFrom alias alias alias alias FunctionDef arguments args NameParam defaults body Assign TupleStore NameStore NameStore NameStore NameStore NameStore NameLoad Assign NameStore Call NameLoad NameLoad Print Str NameLoad Print Str NameLoad Print Str NameLoad Print Str NameLoad Print Str NameLoad Assign NameStore Call NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad Assign NameStore Call NameLoad keyword NameLoad Assign NameStore Call AttributeLoad NameLoad attr ListLoad TupleLoad Str NameLoad TupleLoad Str NameLoad Expr Call AttributeLoad NameLoad attr NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad Return NameLoad decorator_list Assign NameStore Str Assign NameStore Call AttributeLoad NameLoad attr NameLoad Assign NameStore SubscriptLoad NameLoad Index CompareLt AttributeLoad NameLoad attr Num Print Call AttributeLoad Str attr Call NameLoad NameLoad Assign NameStore Str For NameStore Call AttributeLoad NameLoad attr body Assign NameStore SubscriptLoad NameLoad Index Num Assign NameStore SubscriptLoad NameLoad Slice Num Assign NameStore Call NameLoad NameLoad Assign NameStore Call NameLoad NameLoad NameLoad Print Call AttributeLoad Str attr NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr Num Num TryExcept body Assign NameStore Call AttributeLoad NameLoad attr TupleLoad NameLoad NameLoad handlers ExceptHandler type NameLoad body Assign NameStore NameLoad Assert CompareEq SubscriptLoad AttributeLoad NameLoad attr Index Num Call NameLoad NameLoad Assign NameStore Call AttributeLoad NameLoad attr NameLoad keyword Num Assign NameStore Call NameLoad NameLoad NameLoad Print Str NameLoad Expr Str
N/A N/A load a few best settings, train the models, average predictions N/A numpy np N/A pandas pd elm * random_layer * sklearn pipeline sklearn.linear_model Ridge sklearn.metrics mean_squared_error MSE pipeline_driver RMSE load_data x_train y_train x_test y_test get_predictions N/A N/A params N/A N/A N/A N/A n_hidden alpha rbf_width activation_func ridge_alpha params N/A n_hidden N/A int n_hidden N/A n_hidden: n_hidden N/A alpha: alpha N/A rbf_width: rbf_width N/A activation_func: activation_func N/A ridge_alpha: ridge_alpha N/A rl N/A RandomLayer n_hidden n_hidden alpha alpha rbf_width rbf_width activation_func activation_func N/A ridge N/A Ridge alpha ridge_alpha N/A elmr N/A N/A pipeline Pipeline N/A N/A rl rl N/A ridge ridge N/A N/A N/A elmr fit x_train y_train N/A p N/A N/A elmr predict x_test N/A p N/A N/A input_file hyperopt_logs/hyperopt_log_pipeline.csv N/A data N/A N/A pd read_csv input_file N/A best N/A data N/A N/A N/A data rmse 5 N/A N/A N/A training {} models... format N/A len best N/A all_p dummy N/A params N/A N/A best itertuples N/A N/A rmse N/A params N/A 1 N/A params N/A params N/A 2 N/A p N/A get_predictions params N/A new_rmse N/A RMSE y_test p N/A N/A N/A 
{}	{}
 format rmse new_rmse N/A p N/A N/A p reshape -1 1 N/A N/A N/A all_p N/A N/A np hstack N/A all_p p N/A N/A N/A ValueError N/A N/A all_p p N/A N/A N/A N/A all_p shape N/A 1 N/A len best N/A p_bag N/A N/A np mean all_p axis 1 N/A bag_rmse N/A RMSE y_test p_bag N/A bagged RMSE: bag_rmse N/A 
4.80702905174	4.86961396002

4.69688727788	4.71511820023

4.65203836026	4.76711428554

4.90157856325	5.04205983981

4.88192059806	4.90897360006

4.6670679981	4.7602996695

4.79311069383	4.81340706305

4.6723412506	4.65207347166

bagged RMSE: 4.49256467128
