def RMSE(x): return sqrt(x) if __name__ == '__main__': time_step_lag = 6 HORIZON = 9 imfs_count = 0 # set equal to zero for not considering IMFs features data_dir = '/home/long/TTU-SOURCES/self-boosted-ts/data' output_dir = '/home/long/TTU-SOURCES/self-boosted-ts/output/temperature' multi_time_series = load_data_full(data_dir, datasource='temperature', imfs_count=imfs_count) print(multi_time_series.head()) valid_start_dt = '2004-10-30 14:00:00' test_start_dt = '2005-01-16 13:00:00' train_inputs, valid_inputs, test_inputs, y_scaler = split_train_validation_test( multi_time_series, valid_start_time=valid_start_dt, test_start_time=test_start_dt, time_step_lag=time_step_lag, horizon=HORIZON, features=["load"], target=['load'])
def RMSE(x): return sqrt(x) if __name__ == '__main__': time_step_lag = 6 HORIZON = 1 EPOCHS = 50 imfs_count = 0 # set equal to zero for not considering IMFs features data_dir = '/home/long/TTU-SOURCES/self-boosted-ts/data' output_dir = '/home/long/TTU-SOURCES/self-boosted-ts/output/temperature' multi_time_series = load_data_full(data_dir, datasource='electricity', imfs_count=imfs_count) print(multi_time_series.head()) print("count data rows=", multi_time_series.count) valid_start_dt = '2013-05-26 14:15:00' test_start_dt = '2014-03-14 19:15:00' train_inputs, valid_inputs, test_inputs, y_scaler = split_train_validation_test( multi_time_series, valid_start_time=valid_start_dt, test_start_time=test_start_dt, time_step_lag=time_step_lag, horizon=HORIZON, features=["load"],
from sklearn.metrics import mean_squared_log_error from sklearn.metrics import median_absolute_error from sklearn.metrics import r2_score if __name__ == '__main__': time_step_lag = 3 HORIZON = 1 imfs_count = 11 data_dir = 'data' output_dir = 'output/exchange-rate/mtl' multi_time_series = load_data_full(data_dir, datasource='exchange-rate', imfs_count=imfs_count, freq='d') print(multi_time_series.head()) valid_start_dt = '2002-06-18' test_start_dt = '2006-08-13' features = ["load", "imf7", "imf8", "imf9", "imf10"] train_inputs, valid_inputs, test_inputs, y_scaler = split_train_validation_test( multi_time_series, valid_start_time=valid_start_dt, test_start_time=test_start_dt, time_step_lag=time_step_lag, horizon=HORIZON, features=features,