I have this autoencoder:
input_dim = Input(shape=(10,))
encoded1 = Dense(30, activation = 'relu')(input_dim)
encoded2 = Dense(20, activation = 'relu')(encoded1)
encoded3 = Dense(10, activation = 'relu')(encoded2)
encoded4 = Dense(6, activation = 'relu')(encoded3)
decoded1 = Dense(10, activation = 'relu')(encoded4)
decoded2 = Dense(20, activation = 'relu')(decoded1)
decoded3 = Dense(30, activation = 'relu')(decoded2)
decoded4 = Dense(ncol, activation = 'sigmoid')(decoded3)
autoencoder = Model(input = input_dim, output = decoded4)
autoencoder.compile(-...)
autoencoder.fit(...)
Now I would like print or save the features generate in encoded4. Basically, starting from a huge dataset I would like to extract the features generated by autoencoder, after the training part, to obtain a restricted representation of my dataset.
Could you help me?
You can do it by creating the "encoder" model:
encoder = Model(input = input_dim, output = encoded4)
This will use the same layers instances that you trained with the autoencoder and should be producing the feature if you use it in "inference mode" like encoder.predict()
I hope this helps :)
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