July 2017
Beginner to intermediate
715 pages
17h 3m
English
Content preview from Java: Data Science Made Easy
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Configuring the network
The configuration of the network is created using the NeuralNetConfiguration.Builder() class. Ten layers are created where the input layer consists of 1000 neurons. This is larger than the 28 by 28 pixel input and is used to compensate for the sigmoid-belief units used in each layer.
Each of the subsequent layers gets smaller until layer four is reached. This layer represents the last step of the encoding process. With layer five, the decoding process starts and the subsequent layers get bigger. The last layer uses 1000 neurons.
Each layer of the model uses an RBM instance except the last layer, which is constructed using the OutputLayer.Builder class. The configuration code follows:
MultiLayerConfiguration conf ...