Example usage for org.deeplearning4j.eval Evaluation evalTimeSeries

Introduction

In this page you can find the example usage for org.deeplearning4j.eval Evaluation evalTimeSeries.

Prototype

@Deprecated
void evalTimeSeries(INDArray labels, INDArray predicted);

Source Link

Usage

From source file:seqmodel.RNNModel.java

public void evaluate() throws Exception {
    String dataSetBaseDir = prop.getProperty("docvec.dir");
    train = getAMISentenceIterator(dataSetBaseDir + "/train/");
    test = getAMISentenceIterator(dataSetBaseDir + "/test/");

    System.out.println("Traning num_instances: " + train.numExamples());
    System.out.println("Test num_instances: " + test.numExamples());

    //+++ DEBUG://from   w  w w.ja va 2  s  .c om
    //System.out.println("train:");
    //train.reset();
    //while (train.hasNext()) {
    //    System.out.println(train.next());
    //}

    //System.out.println("test:");
    //test.reset();
    //while (test.hasNext()) {
    //    System.out.println(test.next());
    //}
    //--- DEBUG

    MultiLayerNetwork rnn = buildRNN(train);

    for (int i = 0; i < NUM_EPOCHS; i++) {
        System.out.println("Epoch: " + i);
        rnn.fit(train);

        Evaluation evaluation = new Evaluation();
        while (test.hasNext()) {
            DataSet t = test.next();
            INDArray features = t.getFeatureMatrix();
            INDArray lables = t.getLabels();
            //INDArray inMask = t.getFeaturesMaskArray();
            //INDArray outMask = t.getLabelsMaskArray();
            INDArray predicted = null;
            predicted = rnn.output(features, false/*, inMask, outMask*/);

            evaluation.evalTimeSeries(lables, predicted/*, outMask*/);
        }

        train.reset();
        test.reset();

        System.out.println(evaluation.stats());
    }

}

---