Example usage for org.deeplearning4j.text.documentiterator FileLabelAwareIterator hasNextDocument

Introduction

In this page you can find the example usage for org.deeplearning4j.text.documentiterator FileLabelAwareIterator hasNextDocument.

Prototype

@Override
    public boolean hasNextDocument() 

Source Link

Usage

From source file:dollar.learner.smart.ParagraphVectorsClassifierExample.java

License:Apache License

void checkUnlabeledData() throws FileNotFoundException {
    /*/*from  ww w . j a v a 2 s .c om*/
    At this point we assume that we have model built and we can check
    which categories our unlabeled document falls into.
    So we'll start loading our unlabeled documents and checking them
    */
    ClassPathResource unClassifiedResource = new ClassPathResource("paravec/unlabeled");
    FileLabelAwareIterator unClassifiedIterator = new FileLabelAwareIterator.Builder()
            .addSourceFolder(unClassifiedResource.getFile()).build();

    /*
     Now we'll iterate over unlabeled data, and check which label it could be assigned to
     Please note: for many domains it's normal to have 1 document fall into few labels at once,
     with different "weight" for each.
    */
    MeansBuilder meansBuilder = new MeansBuilder(
            (InMemoryLookupTable<VocabWord>) paragraphVectors.getLookupTable(), tokenizerFactory);
    LabelSeeker seeker = new LabelSeeker(iterator.getLabelsSource().getLabels(),
            (InMemoryLookupTable<VocabWord>) paragraphVectors.getLookupTable());

    while (unClassifiedIterator.hasNextDocument()) {
        LabelledDocument document = unClassifiedIterator.nextDocument();
        INDArray documentAsCentroid = meansBuilder.documentAsVector(document);
        List<Pair<String, Double>> scores = seeker.getScores(documentAsCentroid);

        /*
         please note, document.getLabel() is used just to show which document we're looking at now,
         as a substitute for printing out the whole document name.
         So, labels on these two documents are used like titles,
         just to visualize our classification done properly
        */
        log.info("Document '" + document.getLabel() + "' falls into the following categories: ");
        for (Pair<String, Double> score : scores) {
            log.info("        " + score.getFirst() + ": " + score.getSecond());
        }
    }

}

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