You're reading from Java Deep Learning Cookbook

Product typeBook

Published inNov 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781788995207

Edition1st Edition

Languages

Java

Tools

Deeplearning4j TensorFlow

Concepts

Deep Learning

Author (1)

Rahul Raj

Constructing output layers for the network

The output layer design is the last step in configuring the neural network layer. Our aim is to implement a time series prediction model. We need to develop a time series classifier to predict patient mortality. The output layer design should reflect this purpose. In this recipe, we will discuss how to construct the output layer for our use case.

How to do it...

Design the output layer using RnnOutputLayer:

new RnnOutputLayer.Builder(LossFunctions.LossFunction.MCXENT)
 .activation(Activation.SOFTMAX)
 .nIn(LSTM_LAYER_SIZE).nOut(labelCount).build()

Use the addLayer() method to add an output layer to the network configuration:

builder.addLayer("predictMortality", new RnnOutputLayer...

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Java Deep Learning Cookbook

Published in: Nov 2019Publisher: PacktISBN-13: 9781788995207

Author (1)

Rahul Raj

Rahul Raj has more than 7 years of IT industry experience in software development, business analysis, client communication, and consulting on medium-/large-scale projects in multiple domains. Currently, he works as a lead software engineer in a top software development firm. He has extensive experience in development activities comprising requirement analysis, design, coding, implementation, code review, testing, user training, and enhancements. He has written a number of articles about neural networks in Java and they are featured by DL4J/ official Java community channels. He is also a certified machine learning professional, certified by Vskills, the largest government certification body in India.
Read more about Rahul Raj

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