Java Deep Learning Cookbook

How to do it...

1. Use ROC for the model evaluation:

ROC evaluation = new ROC(thresholdSteps);

2. Generate output from features in the test data:

DataSet batch = testDataSetIterator.next(); INDArray[] output = model.output(batch.getFeatures());

3. Use the ROC evaluation instance to perform the evaluation by calling evalTimeseries():

INDArray actuals = batch.getLabels();   INDArray predictions = output[0]   evaluation.evalTimeSeries(actuals, predictions);

4. Display the AUC score (evaluation metrics) by calling calculateAUC():

System.out.println(evaluation.calculateAUC());