I'm working on a face recognition system using the DBN algorithm. when training data, the system will produce an error according to n-epoch. I want to make an error graph plot based on n-epoch
classifier = SupervisedDBNClassification (hidden_layers_structure=[200, 200],
learning_rate_rbm=0.0001,
learning_rate=0.01,
n_epochs_rbm=10,
n_iter_backprop=100,
batch_size=32,
activation_function='relu',
dropout_p = 0.2)
>> Epoch 84 finished ANN training loss 0.681700
>> Epoch 85 finished ANN training loss 0.682314
>> Epoch 86 finished ANN training loss 0.680272
>> Epoch 87 finished ANN training loss 0.680542
Use history = classifier.fit(x_train, y_train)
# list all data in history
print(history.history.keys())
You can access all the information like below to plot a line graph
history.history['acc'])
history.history['val_acc']
history.history['loss'])
history.history['val_loss']
For futher, look at this link
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