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,
