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dataset_best_params.py
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dataset_best_params.py
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problems = {'DriverIdentification': {},
'ConfLongDemo_JSI': {},
'Healthy_Older_People': {},
'Motor_Failure_Time': {},
'Power_consumption': {},
'PRSA2017': {},
'RSSI': {},
'User_Identification_From_Walking': {},
'WISDM': {},
}
problems['DriverIdentification']['dataset'] = './datasets/DriverIdentification/'
problems['DriverIdentification']['n_classes'] = 10
problems['DriverIdentification']['features'] = ['x-accelerometer', 'y-accelerometer', 'z-accelerometer', 'x-gyroscope',
'y-gyroscope', 'z-gyroscope']
problems['DriverIdentification']['sample_rate'] = 2
problems['DriverIdentification']['data_length_time'] = -1
problems['DriverIdentification']['n_h_block'] = 15
problems['DriverIdentification']['n_train_h_block'] = 9
problems['DriverIdentification']['n_valid_h_block'] = 2
problems['DriverIdentification']['n_test_h_block'] = 4
problems['DriverIdentification']['h_moving_step'] = 1
problems['DriverIdentification']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60,
6 * 60, 7 * 60, 8 * 60, 9 * 60, 10 * 60]
problems['DriverIdentification']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60,
6 * 60, 7 * 60]
# problems['DriverIdentification']['KNN']['segments_time'] = 6
# problems['DriverIdentification']['MLP']['segments_time'] = 12
# problems['DriverIdentification']['LR']['segments_time'] = 360
# problems['DriverIdentification']['RF']['segments_time'] = 6
# problems['DriverIdentification']['SVM']['segments_time'] = 720
# problems['DriverIdentification']['CNN']['segments_time'] = 20
# problems['DriverIdentification']['decision_time'] = 4
problems['ConfLongDemo_JSI']['dataset'] = './datasets/ConfLongDemo_JSI/'
problems['ConfLongDemo_JSI']['n_classes'] = 5
problems['ConfLongDemo_JSI']['features'] = ["x", "y", "z"]
problems['ConfLongDemo_JSI']['sample_rate'] = 30
problems['ConfLongDemo_JSI']['data_length_time'] = -1
problems['ConfLongDemo_JSI']['n_h_block'] = 15
problems['ConfLongDemo_JSI']['n_train_h_block'] = 9
problems['ConfLongDemo_JSI']['n_valid_h_block'] = 2
problems['ConfLongDemo_JSI']['n_test_h_block'] = 4
problems['ConfLongDemo_JSI']['h_moving_step'] = 1
problems['ConfLongDemo_JSI']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60]
problems['ConfLongDemo_JSI']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60]
# problems['ConfLongDemo_JSI']['KNN']['segments_time'] = 90
# problems['ConfLongDemo_JSI']['MLP']['segments_time'] = 120
# problems['ConfLongDemo_JSI']['LR']['segments_time'] = 3600
# problems['ConfLongDemo_JSI']['RF']['segments_time'] = 240
# problems['ConfLongDemo_JSI']['SVM']['segments_time'] = 3600
# problems['ConfLongDemo_JSI']['CNN']['segments_time'] = 90
# problems['ConfLongDemo_JSI']['decision_time'] = 4
problems['Healthy_Older_People']['dataset'] = './datasets/Healthy_Older_People/'
problems['Healthy_Older_People']['n_classes'] = 12
problems['Healthy_Older_People']['features'] = ["X", "Y", "Z"]
problems['Healthy_Older_People']['sample_rate'] = 1
problems['Healthy_Older_People']['data_length_time'] = -1
problems['Healthy_Older_People']['n_h_block'] = 15
problems['Healthy_Older_People']['n_train_h_block'] = 9
problems['Healthy_Older_People']['n_valid_h_block'] = 2
problems['Healthy_Older_People']['n_test_h_block'] = 4
problems['Healthy_Older_People']['h_moving_step'] = 1
problems['Healthy_Older_People']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60]
problems['Healthy_Older_People']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60]
# problems['Healthy_Older_People']['KNN']['segments_time'] = 4
# problems['Healthy_Older_People']['MLP']['segments_time'] = 4
# problems['Healthy_Older_People']['LR']['segments_time'] = 30
# problems['Healthy_Older_People']['RF']['segments_time'] = 3
# problems['Healthy_Older_People']['SVM']['segments_time'] = 30
# problems['Healthy_Older_People']['CNN']['segments_time'] = 6
# problems['Healthy_Older_People']['decision_time'] = 2
problems['Motor_Failure_Time']['dataset'] = './datasets/Motor_Failure_Time/'
problems['Motor_Failure_Time']['n_classes'] = 3
problems['Motor_Failure_Time']['features'] = ['x', 'y', 'z']
problems['Motor_Failure_Time']['sample_rate'] = 18
problems['Motor_Failure_Time']['data_length_time'] = -1
problems['Motor_Failure_Time']['n_h_block'] = 15
problems['Motor_Failure_Time']['n_train_h_block'] = 9
problems['Motor_Failure_Time']['n_valid_h_block'] = 2
problems['Motor_Failure_Time']['n_test_h_block'] = 4
problems['Motor_Failure_Time']['h_moving_step'] = 1
problems['Motor_Failure_Time']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60,
6 * 60, 7 * 60, 8 * 60, 9 * 60, 10 * 60]
problems['Motor_Failure_Time']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60,
6 * 60, 7 * 60]
# problems['Motor_Failure_Time']['KNN']['segments_time'] = 54
# problems['Motor_Failure_Time']['MLP']['segments_time'] = 108
# problems['Motor_Failure_Time']['LR']['segments_time'] = 10800
# problems['Motor_Failure_Time']['RF']['segments_time'] = 54
# problems['Motor_Failure_Time']['SVM']['segments_time'] = 10800
# problems['Motor_Failure_Time']['CNN']['segments_time'] = 108
# problems['Motor_Failure_Time']['decision_time'] = 4
problems['Power_consumption']['dataset'] = './datasets/Power_consumption/'
problems['Power_consumption']['n_classes'] = 3
problems['Power_consumption']['features'] = ['Temperature', 'Humidity', 'Wind Speed',
'general diffuse flows', 'diffuse flows',
'Consumption']
problems['Power_consumption']['sample_rate'] = 1
problems['Power_consumption']['data_length_time'] = -1
problems['Power_consumption']['n_h_block'] = 15
problems['Power_consumption']['n_train_h_block'] = 9
problems['Power_consumption']['n_valid_h_block'] = 2
problems['Power_consumption']['n_test_h_block'] = 4
problems['Power_consumption']['h_moving_step'] = 1
problems['Power_consumption']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60,
6 * 60, 7 * 60, 8 * 60, 9 * 60, 10 * 60, 20 * 60, 30 * 60, 40 * 60]
problems['Power_consumption']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60,
6 * 60, 7 * 60, 8 * 60, 9 * 60, 10 * 60, 20 * 60]
# problems['Power_consumption']['KNN']['segments_time'] = 420
# problems['Power_consumption']['MLP']['segments_time'] = 180
# problems['Power_consumption']['LR']['segments_time'] = 60
# problems['Power_consumption']['RF']['segments_time'] = 300
# problems['Power_consumption']['SVM']['segments_time'] = 60
# problems['Power_consumption']['CNN']['segments_time'] = 420
# problems['Power_consumption']['decision_time'] = 30
problems['PRSA2017']['dataset'] = './datasets/PRSA2017/'
problems['PRSA2017']['n_classes'] = 12
problems['PRSA2017']['features'] = ['PM2.5', 'PM10', 'SO2', 'NO2', 'CO', 'O3', 'TEMP', 'PRES', 'DEWP', 'RAIN', 'wd',
'WSPM']
problems['PRSA2017']['sample_rate'] = 1
problems['PRSA2017']['data_length_time'] = -1
problems['PRSA2017']['n_h_block'] = 15
problems['PRSA2017']['n_train_h_block'] = 9
problems['PRSA2017']['n_valid_h_block'] = 2
problems['PRSA2017']['n_test_h_block'] = 4
problems['PRSA2017']['h_moving_step'] = 1
problems['PRSA2017']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60, 6 * 60,
7 * 60, 8 * 60, 9 * 60, 10 * 60, 20 * 60, 30 * 60, 40 * 60]
problems['PRSA2017']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60, 6 * 60,
7 * 60, 8 * 60, 9 * 60, 10 * 60, 20 * 60]
# problems['PRSA2017']['KNN']['segments_time'] = 10
# problems['PRSA2017']['MLP']['segments_time'] = 30
# problems['PRSA2017']['LR']['segments_time'] = 420
# problems['PRSA2017']['RF']['segments_time'] = 3
# problems['PRSA2017']['SVM']['segments_time'] = 30
# problems['PRSA2017']['CNN']['segments_time'] = 60
# problems['PRSA2017']['decision_time'] = 60
problems['RSSI']['dataset'] = './datasets/RSSI/'
problems['RSSI']['n_classes'] = 12
problems['RSSI']['features'] = ['rssiOne', 'rssiTwo']
problems['RSSI']['sample_rate'] = 1
problems['RSSI']['data_length_time'] = -1
problems['RSSI']['n_h_block'] = 6
problems['RSSI']['n_train_h_block'] = 4
problems['RSSI']['n_valid_h_block'] = 1
problems['RSSI']['n_test_h_block'] = 1
problems['RSSI']['h_moving_step'] = 1
problems['RSSI']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60]
problems['RSSI']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60]
# problems['RSSI']['KNN']['segments_time'] = 120
# problems['RSSI']['MLP']['segments_time'] = 30
# problems['RSSI']['LR']['segments_time'] = 60
# problems['RSSI']['RF']['segments_time'] = 3
# problems['RSSI']['SVM']['segments_time'] = 60
# problems['RSSI']['CNN']['segments_time'] = 30
# problems['RSSI']['decision_time'] = 4
problems['User_Identification_From_Walking']['dataset'] = './datasets/User_Identification_From_Walking/'
problems['User_Identification_From_Walking']['n_classes'] = 13
problems['User_Identification_From_Walking']['features'] = [' x acceleration', ' y acceleration', ' z acceleration']
problems['User_Identification_From_Walking']['sample_rate'] = 32
problems['User_Identification_From_Walking']['data_length_time'] = -1
problems['User_Identification_From_Walking']['n_h_block'] = 10
problems['User_Identification_From_Walking']['n_train_h_block'] = 5
problems['User_Identification_From_Walking']['n_valid_h_block'] = 2
problems['User_Identification_From_Walking']['n_test_h_block'] = 3
problems['User_Identification_From_Walking']['h_moving_step'] = 1
problems['User_Identification_From_Walking']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 21, 22, 23, 24]
problems['User_Identification_From_Walking']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]
# problems['User_Identification_From_Walking']['KNN']['segments_time'] = 96
# problems['User_Identification_From_Walking']['MLP']['segments_time'] = 96
# problems['User_Identification_From_Walking']['LR']['segments_time'] = 256
# problems['User_Identification_From_Walking']['RF']['segments_time'] = 96
# problems['User_Identification_From_Walking']['SVM']['segments_time'] = 576
# problems['User_Identification_From_Walking']['CNN']['segments_time'] = 96
# problems['DriverIdentification']['decision_time'] = 4
problems['WISDM']['dataset'] = './datasets/WISDM/'
problems['WISDM']['n_classes'] = 10
problems['WISDM']['features'] = ['X-accel', 'Y-accel', 'Z-accel']
problems['WISDM']['sample_rate'] = 20
problems['WISDM']['data_length_time'] = -1
problems['WISDM']['n_h_block'] = 15
problems['WISDM']['n_train_h_block'] = 9
problems['WISDM']['n_valid_h_block'] = 4
problems['WISDM']['n_test_h_block'] = 2
problems['WISDM']['h_moving_step'] = 1
problems['WISDM']['decision_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60, 6 * 60, 7 * 60,
8 * 60, 9 * 60, 10 * 60]
problems['WISDM']['segments_times'] = [3, 4, 5, 6, 7, 8, 9, 10, 30, 60, 2 * 60, 3 * 60, 4 * 60, 5 * 60, 6 * 60, 7 * 60]
# problems['WISDM']['KNN']['segments_time'] = 60
# problems['WISDM']['MLP']['segments_time'] = 80
# problems['WISDM']['LR']['segments_time'] = 1200
# problems['WISDM']['RF']['segments_time'] = 60
# problems['WISDM']['SVM']['segments_time'] = 180
# problems['WISDM']['CNN']['segments_time'] = 160
# problems['WISDM']['decision_time'] = 4