Example usage for org.apache.mahout.cf.taste.impl.recommender.svd ALSWRFactorizer ALSWRFactorizer

Introduction

In this page you can find the example usage for org.apache.mahout.cf.taste.impl.recommender.svd ALSWRFactorizer ALSWRFactorizer.

Prototype

public ALSWRFactorizer(DataModel dataModel, int numFeatures, double lambda, int numIterations,
            boolean usesImplicitFeedback, double alpha, int numTrainingThreads) throws TasteException 

Source Link

Usage

From source file:org.plista.kornakapi.core.training.FactorizationbasedInMemoryTrainer.java

License:Apache License

@Override
protected void doTrain(File targetFile, DataModel inmemoryData, int numProcessors) throws IOException {
    try {//from   ww  w .  j a v a 2  s .  c  o m
        if (inmemoryData.getNumItems() >= 5 && inmemoryData.getNumUsers() >= 10) {//preventing matrix singularity
            ALSWRFactorizer factorizer = new ALSWRFactorizer(inmemoryData, conf.getNumberOfFeatures(),
                    conf.getLambda(), conf.getNumberOfIterations(), conf.isUsesImplicitFeedback(),
                    conf.getAlpha(), numProcessors);

            long start = System.currentTimeMillis();
            Factorization factorization = factorizer.factorize();
            long estimateDuration = System.currentTimeMillis() - start;

            if (log.isInfoEnabled()) {
                log.info("Model trained in {} ms", estimateDuration);
            }

            new FilePersistenceStrategy(targetFile).maybePersist(factorization);
        }
    } catch (Exception e) {
        throw new IOException(e);
    }
}

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