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cerlymarco / MEDIUM_NoteBook

Repository containing notebooks of my posts on Medium
MIT License
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Features for autoencoder #10

Closed debmalya97 closed 4 years ago

debmalya97 commented 4 years ago 
X = np.concatenate([X_train_c,X_train_o,X_test_c,X_test_o],axis=0)
sequence_autoencoder.fit(X[:len(X_train_c)+len(X_train_o)], X[:len(X_train_c)+len(X_train_o)], 
                         batch_size=128, epochs=100, verbose=2, shuffle=True)

I was going through the extreme forecasting code and I saw that you used only the sequence of average price as an input to the auto encoder. I was wondering why didn't you use the extra features as well in the input to the autoencoder? According to my knowledge autoencoder is used to learn a complex representation of the feature space so including more features should help it.

Thanks in advance.

cerlymarco commented 4 years ago

Hi, you are right, this is correct but it's not in my purpose. Consider to star or fork the repository if you consider it useful All the best