Example usage for org.apache.mahout.math Matrix setQuick

Introduction

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

Prototype

void setQuick(int row, int column, double value);

Source Link

Document

Set the value at the given index, without checking bounds

Usage

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

License:Apache License

static Matrix addLambdaTimesNuiTimesE(Matrix matrix, double lambda, int nui) {
    Preconditions.checkArgument(matrix.numCols() == matrix.numRows(), "Must be a Square Matrix");
    double lambdaTimesNui = lambda * nui;
    int numCols = matrix.numCols();
    for (int n = 0; n < numCols; n++) {
        matrix.setQuick(n, n, matrix.getQuick(n, n) + lambdaTimesNui);
    }//from   www  .ja  v a2  s  .c  o  m
    return matrix;
}

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

License:Apache License

/** Y' (Cu - I) Y +  I */
private Matrix getYtransponseCuMinusIYPlusLambdaI(Vector userRatings) {
    Preconditions.checkArgument(userRatings.isSequentialAccess(), "need sequential access to ratings!");

    /* (Cu -I) Y */
    OpenIntObjectHashMap<Vector> CuMinusIY = new OpenIntObjectHashMap<Vector>(
            userRatings.getNumNondefaultElements());
    for (Element e : userRatings.nonZeroes()) {
        CuMinusIY.put(e.index(), Y.get(e.index()).times(confidence(e.get()) - 1));
    }//w w  w . j av a2  s .  co m

    Matrix YtransponseCuMinusIY = new DenseMatrix(numFeatures, numFeatures);

    /* Y' (Cu -I) Y by outer products */
    for (Element e : userRatings.nonZeroes()) {
        for (Vector.Element feature : Y.get(e.index()).all()) {
            Vector partial = CuMinusIY.get(e.index()).times(feature.get());
            YtransponseCuMinusIY.viewRow(feature.index()).assign(partial, Functions.PLUS);
        }
    }

    /* Y' (Cu - I) Y +  I  add lambda on the diagonal */
    for (int feature = 0; feature < numFeatures; feature++) {
        YtransponseCuMinusIY.setQuick(feature, feature,
                YtransponseCuMinusIY.getQuick(feature, feature) + lambda);
    }

    return YtransponseCuMinusIY;
}

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From source file:com.skp.experiment.math.als.hadoop.DistributedImplicitFeedbackAlternatingLeastSquaresSolver.java

License:Apache License

public Vector solve(Vector userRatings) throws IOException {
    Preconditions.checkArgument(userRatings.isSequentialAccess(), "need sequential access to ratings!");
    //Matrix sparseY = getSparseMatrix(userRatings);
    getSparseMatrix(userRatings);/*from www .  j  ava2  s.com*/
    /* Y' (Cu - I) Y +  I */
    /* Y' Cu p(u) */
    Vector YtransponseCuPu = new DenseVector(numFeatures);
    /* (Cu -I) Y */
    OpenIntObjectHashMap<Vector> CuMinusIY = new OpenIntObjectHashMap<Vector>();

    Iterator<Vector.Element> ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        CuMinusIY.put(e.index(), sparseY.get(e.index()).times(confidence(e.get()) - 1));
        /* Y' Cu p(u) */
        YtransponseCuPu.assign(sparseY.get(e.index()).times(confidence(e.get())), Functions.PLUS);
    }

    Matrix YtransponseCuMinusIY = new DenseMatrix(numFeatures, numFeatures);

    /* Y' (Cu -I) Y by outer products */
    ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        for (Vector.Element feature : sparseY.get(e.index())) {
            Vector partial = CuMinusIY.get(e.index()).times(feature.get());
            YtransponseCuMinusIY.viewRow(feature.index()).assign(partial, Functions.PLUS);
        }
    }

    /* Y' (Cu - I) Y +  I  add lambda on the diagonal */
    for (int feature = 0; feature < numFeatures; feature++) {
        YtransponseCuMinusIY.setQuick(feature, feature,
                YtransponseCuMinusIY.getQuick(feature, feature) + lambda);
    }

    Matrix YtransposeCuPu = columnVectorAsMatrix(YtransponseCuPu);
    return solve(YtransposeY.plus(YtransponseCuMinusIY), YtransposeCuPu);
    //return YtransponseCuMinusIY;
}

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From source file:com.skp.experiment.math.als.hadoop.DistributedImplicitFeedbackAlternatingLeastSquaresSolver.java

License:Apache License

private Matrix columnVectorAsMatrix(Vector v) {
    Matrix matrix = new DenseMatrix(numFeatures, 1);
    for (Vector.Element e : v) {
        matrix.setQuick(e.index(), 0, e.get());
    }/*from w  ww  .j av  a  2 s.co m*/
    return matrix;
}

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From source file:com.skp.experiment.math.als.hadoop.ImplicitFeedbackAlternatingLeastSquaresReasonSolver.java

License:Apache License

/** Y' (Cu - I) Y +  I */
private Matrix YtransponseCuMinusIYPlusLambdaI(Vector userRatings) {
    Preconditions.checkArgument(userRatings.isSequentialAccess(), "need sequential access to ratings!");

    /* (Cu -I) Y */
    OpenIntObjectHashMap<Vector> CuMinusIY = new OpenIntObjectHashMap<Vector>();
    Iterator<Vector.Element> ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        CuMinusIY.put(e.index(), Y.get(e.index()).times(confidence(e.get()) - 1));
    }/*w w  w. j  a  v a 2  s  .c  om*/

    Matrix YtransponseCuMinusIY = new DenseMatrix(numFeatures, numFeatures);

    /* Y' (Cu -I) Y by outer products */
    ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        for (Vector.Element feature : Y.get(e.index())) {
            Vector partial = CuMinusIY.get(e.index()).times(feature.get());
            YtransponseCuMinusIY.viewRow(feature.index()).assign(partial, Functions.PLUS);
        }
    }

    /* Y' (Cu - I) Y +  I  add lambda on the diagonal */
    for (int feature = 0; feature < numFeatures; feature++) {
        YtransponseCuMinusIY.setQuick(feature, feature,
                YtransponseCuMinusIY.getQuick(feature, feature) + lambda);
    }

    return YtransponseCuMinusIY;
}

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From source file:com.skp.experiment.math.als.hadoop.ImplicitFeedbackAlternatingLeastSquaresSolver.java

License:Apache License

/** Y' (Cu - I) Y +  I */
private Matrix YtransponseCuMinusIYPlusLambdaI(Vector userRatings) {
    Preconditions.checkArgument(userRatings.isSequentialAccess(), "need sequential access to ratings!");

    /* (Cu -I) Y */
    OpenIntObjectHashMap<Vector> CuMinusIY = new OpenIntObjectHashMap<Vector>();
    Iterator<Vector.Element> ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        CuMinusIY.put(e.index(), Y.viewRow(e.index()).times(confidence(e.get()) - 1));
        //CuMinusIY.put(e.index(), Y.get(e.index()).times(confidence(e.get()) - 1));
    }/*from   w  ww  .jav  a2  s . c  om*/

    Matrix YtransponseCuMinusIY = new DenseMatrix(numFeatures, numFeatures);

    /* Y' (Cu -I) Y by outer products */
    ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        //for (Vector.Element feature : Y.get(e.index())) {
        for (Vector.Element feature : Y.viewRow(e.index())) {
            Vector partial = CuMinusIY.get(e.index()).times(feature.get());
            YtransponseCuMinusIY.viewRow(feature.index()).assign(partial, Functions.PLUS);
        }
    }

    /* Y' (Cu - I) Y +  I  add lambda on the diagonal */
    for (int feature = 0; feature < numFeatures; feature++) {
        YtransponseCuMinusIY.setQuick(feature, feature,
                YtransponseCuMinusIY.getQuick(feature, feature) + lambda);
    }

    return YtransponseCuMinusIY;
}

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From source file:com.ydy.cf.solver.impl.AlternatingLeastSquaresImplicitSolver.java

License:Apache License

/** Y' (Cu - I) Y +  I */
private Matrix YtransponseCuMinusIYPlusLambdaI(Vector userRatings) {
    Preconditions.checkArgument(userRatings.isSequentialAccess(), "need sequential access to ratings!");

    /* (Cu -I) Y */
    OpenIntObjectHashMap<Vector> CuMinusIY = new OpenIntObjectHashMap<Vector>();
    Iterator<Vector.Element> ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        Vector curYRow = Y.viewRow(e.index());
        CuMinusIY.put(e.index(), curYRow.times(confidence(e.get()) - 1));
    }/*from  w w w  .j  a  va2 s . co  m*/

    Matrix YtransponseCuMinusIY = new DenseMatrix(numFeatures, numFeatures);

    /* Y' (Cu -I) Y by outer products */
    ratings = userRatings.iterateNonZero();
    while (ratings.hasNext()) {
        Vector.Element e = ratings.next();
        for (Vector.Element feature : Y.viewRow(e.index())) {
            Vector partial = CuMinusIY.get(e.index()).times(feature.get());
            YtransponseCuMinusIY.viewRow(feature.index()).assign(partial, Functions.PLUS);
        }
    }

    /* Y' (Cu - I) Y +  I  add lambda on the diagonal */
    for (int feature = 0; feature < numFeatures; feature++) {
        YtransponseCuMinusIY.setQuick(feature, feature,
                YtransponseCuMinusIY.getQuick(feature, feature) + lambda);
    }

    return YtransponseCuMinusIY;
}

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From source file:com.ydy.cf.solver.impl.AlternatingLeastSquaresSolver.java

License:Apache License

private Matrix addLambdaTimesNuiTimesE(Matrix matrix, double lambda, int nui) {
    Preconditions.checkArgument(matrix.numCols() == matrix.numRows());
    for (int n = 0; n < matrix.numCols(); n++) {
        matrix.setQuick(n, n, matrix.getQuick(n, n) + lambda * nui);
    }//from w  w  w  . j a  va 2 s. c o m
    return matrix;
}

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From source file:com.ydy.cf.solver.impl.AlternatingLeastSquaresSolver.java

License:Apache License

private Matrix createMiIi(Iterable<Vector> featureVectors, int numFeatures) {
    Matrix MiIi = new DenseMatrix(numFeatures, Iterables.size(featureVectors));
    int n = 0;/*from   www.ja va 2 s  .  com*/
    for (Vector featureVector : featureVectors) {
        for (int m = 0; m < numFeatures; m++) {
            MiIi.setQuick(m, n, featureVector.getQuick(m));
        }
        n++;
    }
    return MiIi;
}

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From source file:com.ydy.cf.solver.impl.AlternatingLeastSquaresSolver.java

License:Apache License

private Matrix createRiIiMaybeTransposed(Vector ratingVector) {
    Preconditions.checkArgument(ratingVector.isSequentialAccess());
    Matrix RiIiMaybeTransposed = new DenseMatrix(ratingVector.getNumNondefaultElements(), 1);
    Iterator<Vector.Element> ratingsIterator = ratingVector.iterateNonZero();
    int index = 0;
    while (ratingsIterator.hasNext()) {
        Vector.Element elem = ratingsIterator.next();
        RiIiMaybeTransposed.setQuick(index++, 0, elem.get());
    }//from w ww . j av  a  2  s  . com
    return RiIiMaybeTransposed;
}

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