Commit 5cda2853 authored by Ard Kastrati's avatar Ard Kastrati
Browse files

Added the inceptionTime results with no shuffling for ETRA

parent cf19904c
......@@ -42,8 +42,7 @@ Cluster can be set to clustering(), clustering2() or clustering3(), where differ
"""
# Choosing model
config['model'] = 'eegnet'
config['model'] = 'cnn'
config['model'] = 'inception'
config['downsampled'] = False
config['split'] = False
config['cluster'] = clustering()
......
......@@ -18,7 +18,7 @@ def main():
logging.info('Started the Logging')
start_time = time.time()
# try:
# trainX, trainY = IOHelper.get_mat_data(config['data_dir'], verbose=True)
trainX, trainY = IOHelper.get_mat_data(config['data_dir'], verbose=True)
# if config['model'] == 'eegnet' or config['model'] == 'eegnet_cluster':
# trainX = np.transpose(trainX, (0, 2, 1))
......@@ -26,9 +26,9 @@ def main():
# tune(trainX,trainY)
# run(trainX,trainY)
run(trainX,trainY)
# select_best_model()
comparison_plot_loss()
# comparison_plot_loss()
logging.info("--- Runtime: %s seconds ---" % (time.time() - start_time))
logging.info('Finished Logging')
......
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best_model_train_loss,best_model_val_loss,best_model_train_acc,best_model_val_acc
0.01928609237074852,0.15049758553504944,0.993760347366333,0.9424809424809425
loss,accuracy,val_loss,val_accuracy
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0.13244186341762543,0.9461182951927185,0.17744697630405426,0.9325017325017325
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0.05435468629002571,0.9783852696418762,0.17434537410736084,0.9331947331947332
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0.04096753150224686,0.9843836426734924,0.1594633162021637,0.934996534996535
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0.022229192778468132,0.9920021891593933,0.1692405790090561,0.9334719334719335
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INFO:root:Started the Logging
INFO:root:X training loaded.
INFO:root:(129, 500, 36223)
INFO:root:y training loaded.
INFO:root:(1, 36223)
INFO:root:Setting the shapes
INFO:root:(36223, 500, 129)
INFO:root:(36223, 1)
INFO:root:Started running inception. If you want to run other methods please choose another model in the config.py file.
INFO:root:Parameters:
INFO:root:--------------- use residual : True
INFO:root:--------------- depth : 12
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 64
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:--------------- bottleneck_size : 16
INFO:root:Parameters:
INFO:root:--------------- use residual : True
INFO:root:--------------- depth : 12
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 64
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:--------------- bottleneck_size : 16
INFO:root:Parameters:
INFO:root:--------------- use residual : True
INFO:root:--------------- depth : 12
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 64
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:--------------- bottleneck_size : 16
INFO:root:Parameters:
INFO:root:--------------- use residual : True
INFO:root:--------------- depth : 12
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 64
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:--------------- bottleneck_size : 16
INFO:root:Parameters:
INFO:root:--------------- use residual : True
INFO:root:--------------- depth : 12
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 64
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:--------------- bottleneck_size : 16
INFO:root:**********
INFO:root:--- Runtime: 10901.414864778519 seconds ---
INFO:root:Finished Logging
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