Java Deep Learning Cookbook

How to do it...

1. Compose a map that relates each MNIST digit to a list of (score, feature) pairs:

Map<Integer,List<Pair<Double,INDArray>>> listsByDigit = new HashMap<>();

2. Iterate through each and every test feature, calculate the reconstruction error, make a score-feature pair for the purpose of displaying the sample with a low reconstruction error:

for( int i=0; i<featuresTest.size(); i++ ){ INDArray testData = featuresTest.get(i); INDArray labels = labelsTest.get(i); for( int j=0; j<testData.rows(); j++){ INDArray example = testData.getRow(j, true); int digit = (int)labels.getDouble(j); double score = net.score(new DataSet(example,example)); // Add (score, example) pair to the appropriate list List digitAllPairs = listsByDigit.get(digit); ...