Example usage for org.apache.mahout.math DenseVector DenseVector

Introduction

In this page you can find the example usage for org.apache.mahout.math DenseVector DenseVector.

Prototype

public DenseVector(DenseVector values, boolean shallowCopy) 

Source Link

Usage

From source file:com.innometrics.integration.app.recommender.ml.als.ALSWRFactorizer.java

License:Apache License

protected static Vector ratingVector(PreferenceArray prefs) {
    double[] ratings = new double[prefs.length()];
    for (int n = 0; n < prefs.length(); n++) {
        ratings[n] = prefs.get(n).getValue();
    }/*from  w  w  w.j  a  va 2 s .  c  o m*/
    return new DenseVector(ratings, true);
}

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From source file:com.innometrics.integration.app.recommender.ml.als.ALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> itemFeaturesMapping(LongPrimitiveIterator itemIDs, int numItems,
        double[][] featureMatrix) {
    OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<Vector>(numItems);
    while (itemIDs.hasNext()) {
        long itemID = itemIDs.next();
        int itemIndex = itemIndex(itemID);
        mapping.put(itemIndex, new DenseVector(featureMatrix[itemIndex(itemID)], true));
    }/*from w  ww.  j av  a2s  .  co  m*/

    return mapping;
}

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From source file:com.innometrics.integration.app.recommender.ml.als.ALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> userFeaturesMapping(LongPrimitiveIterator userIDs, int numUsers,
        double[][] featureMatrix) {
    OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<Vector>(numUsers);

    while (userIDs.hasNext()) {
        long userID = userIDs.next();
        int userIndex = userIndex(userID);
        mapping.put(userIndex, new DenseVector(featureMatrix[userIndex(userID)], true));
    }// w  w  w .  j a  v  a  2 s.  c om

    return mapping;
}

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From source file:org.codelibs.elasticsearch.taste.recommender.svd.ALSWRFactorizer.java

License:Apache License

protected static Vector ratingVector(final PreferenceArray prefs) {
    final double[] ratings = new double[prefs.length()];
    for (int n = 0; n < prefs.length(); n++) {
        ratings[n] = prefs.get(n).getValue();
    }/*  w  w  w .ja  v  a2s .  c om*/
    return new DenseVector(ratings, true);
}

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From source file:org.codelibs.elasticsearch.taste.recommender.svd.ALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> itemFeaturesMapping(final LongPrimitiveIterator itemIDs,
        final int numItems, final double[][] featureMatrix) {
    final OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<Vector>(numItems);
    while (itemIDs.hasNext()) {
        final long itemID = itemIDs.next();
        mapping.put((int) itemID, new DenseVector(featureMatrix[itemIndex(itemID)], true));
    }/*from w w  w  . j  av a  2s .c  o  m*/

    return mapping;
}

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From source file:org.codelibs.elasticsearch.taste.recommender.svd.ALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> userFeaturesMapping(final LongPrimitiveIterator userIDs,
        final int numUsers, final double[][] featureMatrix) {
    final OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<Vector>(numUsers);

    while (userIDs.hasNext()) {
        final long userID = userIDs.next();
        mapping.put((int) userID, new DenseVector(featureMatrix[userIndex(userID)], true));
    }/*from  ww  w  . j  a va  2 s  .c  om*/

    return mapping;
}

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From source file:org.gpfvic.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> itemFeaturesMapping(LongPrimitiveIterator itemIDs, int numItems,
        double[][] featureMatrix) {
    OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<>(numItems);
    while (itemIDs.hasNext()) {
        long itemID = itemIDs.next();
        int itemIndex = itemIndex(itemID);
        mapping.put(itemIndex, new DenseVector(featureMatrix[itemIndex(itemID)], true));
    }/*  w  w w.  j  av  a 2 s . c om*/

    return mapping;
}

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From source file:org.gpfvic.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> userFeaturesMapping(LongPrimitiveIterator userIDs, int numUsers,
        double[][] featureMatrix) {
    OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<>(numUsers);

    while (userIDs.hasNext()) {
        long userID = userIDs.next();
        int userIndex = userIndex(userID);
        mapping.put(userIndex, new DenseVector(featureMatrix[userIndex(userID)], true));
    }//  w  ww  .ja v  a2  s  .c  om

    return mapping;
}

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From source file:org.plista.kornakapi.core.optimizer.ErrorALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> itemFeaturesMapping(LongPrimitiveIterator itemIDs, int numItems,
        double[][] featureMatrix) {
    OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<Vector>(numItems);
    while (itemIDs.hasNext()) {
        long itemID = itemIDs.next();
        mapping.put((int) itemID, new DenseVector(featureMatrix[itemIndex(itemID)], true));
    }//from w w  w .ja va  2 s  .co m

    return mapping;
}

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From source file:org.plista.kornakapi.core.optimizer.ErrorALSWRFactorizer.java

License:Apache License

protected OpenIntObjectHashMap<Vector> userFeaturesMapping(LongPrimitiveIterator userIDs, int numUsers,
        double[][] featureMatrix) {
    OpenIntObjectHashMap<Vector> mapping = new OpenIntObjectHashMap<Vector>(numUsers);

    while (userIDs.hasNext()) {
        long userID = userIDs.next();
        mapping.put((int) userID, new DenseVector(featureMatrix[userIndex(userID)], true));
    }/*  w  w  w .  j a v  a 2s  . co m*/

    return mapping;
}

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