Other evaluations are available through the DL4J API. This section lists them.
It is possible to evaluate a network performing regression through the RegressionEvaluation class (https://static.javadoc.io/org.deeplearning4j/deeplearning4j-nn/1.0.0-alpha/org/deeplearning4j/eval/RegressionEvaluation.html, DL4J NN). With reference to the example that we used in the Evaluation for classification section, evaluation for regression can be done the following way:
val eval = new RegressionEvaluation(3)
val output = model.output(testData.getFeatureMatrix)
eval.eval(testData.getLabels, output)
println(eval.stats)
The produced output of the stats method includes the MSE, the MAE, the RMSE, the RSE, and the R^2:

ROC (short for Receiver Operating Characteristic, https://en.wikipedia.org/wiki/Receiver_operating_characteristic) is another commonly used metric for the...