October 2017
Beginner to intermediate
572 pages
26h 1m
English
Similar to other classification methods, we can predict the labels of new observations based on trained neural networks. Furthermore, we can validate the performance of these networks through the use of a confusion matrix. In the following recipe, we will introduce how to use the compute function in a neural network to obtain a probability matrix of the testing dataset labels, and use a table and confusion matrix to measure the prediction performance.
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