Examples of Factorizer

org.apache.mahout.cf.taste.impl.recommender.svd.Factorizer
Implementation must be able to create a factorization of a rating matrix

Examples of org.apache.mahout.cf.taste.impl.recommender.svd.Factorizer




    KDDCupFactorizablePreferences factorizablePreferences =
        new KDDCupFactorizablePreferences(KDDCupDataModel.getTrainingFile(dataFileDirectory));


    Factorizer sgdFactorizer = new ParallelArraysSGDFactorizer(factorizablePreferences, numFeatures, numIterations,
        learningRate, preventOverfitting, randomNoise);


    Factorization factorization = sgdFactorizer.factorize();


    log.info("Estimating validation preferences...");
    int prefsProcessed = 0;
    RunningAverage average = new FullRunningAverage();
    for (Pair<PreferenceArray,long[]> validationPair

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Examples of org.apache.mahout.cf.taste.impl.recommender.svd.Factorizer




    KDDCupFactorizablePreferences factorizablePreferences =
        new KDDCupFactorizablePreferences(KDDCupDataModel.getTrainingFile(dataFileDirectory));


    Factorizer sgdFactorizer = new ParallelArraysSGDFactorizer(factorizablePreferences, numFeatures, numIterations,
        learningRate, preventOverfitting, randomNoise);


    Factorization factorization = sgdFactorizer.factorize();


    log.info("Estimating validation preferences...");
    int prefsProcessed = 0;
    RunningAverage average = new FullRunningAverage();
    DataFileIterable validations = new DataFileIterable(KDDCupDataModel.getValidationFile(dataFileDirectory));

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Examples of org.apache.mahout.cf.taste.impl.recommender.svd.Factorizer




    KDDCupFactorizablePreferences factorizablePreferences =
        new KDDCupFactorizablePreferences(KDDCupDataModel.getTrainingFile(dataFileDirectory));


    Factorizer sgdFactorizer = new ParallelArraysSGDFactorizer(factorizablePreferences, numFeatures, numIterations,
        learningRate, preventOverfitting, randomNoise);


    Factorization factorization = sgdFactorizer.factorize();


    log.info("Estimating validation preferences...");
    int prefsProcessed = 0;
    RunningAverage average = new FullRunningAverage();
    for (Pair<PreferenceArray,long[]> validationPair :

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