Java: Data Science Made Easy

Evaluating the model

In the next sequence of code, we evaluate the model against the training dataset. An Evaluation instance is created using an argument specifying that there are four classes. The test data is fed into the model using the output method. The eval method takes the output of the model and compares it against the test data classes to generate statistics. The getLabels method returns the expected values:

Evaluation evaluation = new Evaluation(4); INDArray output = model.output(testData.getFeatureMatrix()); evaluation.eval(testData.getLabels(), output); out.println(evaluation.stats()); 

The output of the training follows, which is produced by the ScoreIterationListener class. However, the values you get may differ due to how ...