Examples with DenseVector org.apache.mahout.math.DenseVector used on opensource projects

Example 31 with DenseVector

use of org.apache.mahout.math.DenseVector in project pyramid by cheng-li.

the class Weights method readObject.

private void readObject(java.io.ObjectInputStream in) throws IOException, ClassNotFoundException {
    numClasses = in.readInt();
    numFeatures = in.readInt();
    int[] indices = (int[]) in.readObject();
    double[] values = (double[]) in.readObject();
    weightVector = new DenseVector((numFeatures + 1) * numClasses);
    for (int i = 0; i < indices.length; i++) {
        weightVector.set(indices[i], values[i]);
    }
}

Example 32 with DenseVector

use of org.apache.mahout.math.DenseVector in project pyramid by cheng-li.

the class RidgeBinaryLogisticLoss method Hv.

public void Hv(Vector s, Vector Hs) {
    Vector wa = new DenseVector(numRows);
    Xv(s, wa);
    for (int i = 0; i < numRows; i++) wa.set(i, regularization.get(i) * diagonals.get(i) * wa.get(i));
    XTv(wa, Hs);
    for (int i = 0; i < numColumns; i++) Hs.set(i, s.get(i) + Hs.get(i));
// delete[] wa;
}

Example 33 with DenseVector

use of org.apache.mahout.math.DenseVector in project pyramid by cheng-li.

the class StandardFormat method save.

public static void save(MultiLabelClfDataSet dataSet, File featureFile, File labelFile, String delimiter) throws Exception {
    int numDataPoints = dataSet.getNumDataPoints();
    int numFeatures = dataSet.getNumFeatures();
    int numClasses = dataSet.getNumClasses();
    featureFile.getParentFile().mkdirs();
    labelFile.getParentFile().mkdirs();
    try (BufferedWriter bw1 = new BufferedWriter(new FileWriter(featureFile))) {
        for (int i = 0; i < numDataPoints; i++) {
            Vector vector = dataSet.getRow(i);
            Vector dense = new DenseVector(vector);
            for (int j = 0; j < numFeatures; j++) {
                bw1.write("" + dense.get(j));
                if (j != numFeatures - 1) {
                    bw1.write(delimiter);
                } else {
                    bw1.write("\n");
                }
            }
        }
    }
    try (BufferedWriter bw2 = new BufferedWriter(new FileWriter(labelFile))) {
        MultiLabel[] labels = dataSet.getMultiLabels();
        for (int i = 0; i < numDataPoints; i++) {
            MultiLabel label = labels[i];
            for (int l = 0; l < numClasses; l++) {
                if (label.matchClass(l)) {
                    bw2.write("" + 1);
                } else {
                    bw2.write("" + 0);
                }
                if (l < numClasses - 1) {
                    bw2.write(delimiter);
                }
            }
            bw2.write("\n");
        }
    }
}

Example 34 with DenseVector

use of org.apache.mahout.math.DenseVector in project pyramid by cheng-li.

the class BMSelectorTest method test1.

private static void test1() {
    DataSet dataSet = DataSetBuilder.getBuilder().numFeatures(5).numDataPoints(20).dense(true).build();
    for (int i = 0; i < 5; i++) {
        dataSet.setFeatureValue(i, 0, 1);
    }
    for (int i = 5; i < 10; i++) {
        dataSet.setFeatureValue(i, 1, 1);
    }
    for (int i = 10; i < 20; i++) {
        dataSet.setFeatureValue(i, 1, 1);
        dataSet.setFeatureValue(i, 2, 1);
        dataSet.setFeatureValue(i, 3, 1);
    }
    System.out.println("dataset = " + dataSet);
    BM bm = BMSelector.select(dataSet, 3, 10);
    System.out.println(bm);
    for (int i = 0; i < 5; i++) {
        System.out.println("sample " + i);
        System.out.println(bm.sample());
    }
    Vector vector1 = new DenseVector(5);
    vector1.set(0, 1);
    Vector vector2 = new DenseVector(5);
    vector2.set(1, 1);
    Vector vector3 = new DenseVector(5);
    vector3.set(1, 1);
    vector3.set(2, 1);
    vector3.set(3, 1);
    System.out.println(Math.exp(bm.logProbability(vector1)));
    System.out.println(Math.exp(bm.logProbability(vector2)));
    System.out.println(Math.exp(bm.logProbability(vector3)));
}

Example 35 with DenseVector

use of org.apache.mahout.math.DenseVector in project pyramid by cheng-li.

the class BMTrainerTest method test5.

private static void test5() {
    DataSet dataSet = DataSetBuilder.getBuilder().numFeatures(5).numDataPoints(20).dense(true).build();
    for (int i = 0; i < 5; i++) {
        dataSet.setFeatureValue(i, 0, 1);
    }
    for (int i = 5; i < 10; i++) {
        dataSet.setFeatureValue(i, 1, 1);
    }
    for (int i = 10; i < 20; i++) {
        dataSet.setFeatureValue(i, 2, 1);
        dataSet.setFeatureValue(i, 3, 1);
    }
    System.out.println("dataset = " + dataSet);
    BMTrainer trainer = new BMTrainer(dataSet, 3, 0);
    System.out.println(trainer.bm);
    trainer.train();
    // for (int iter=0;iter<100;iter++){
    // trainer.iterate();
    // }
    System.out.println(trainer.bm);
    Vector vector1 = new DenseVector(5);
    vector1.set(0, 1);
    Vector vector2 = new DenseVector(5);
    vector2.set(1, 1);
    Vector vector3 = new DenseVector(5);
    vector3.set(2, 1);
    vector3.set(3, 1);
    System.out.println(Math.exp(trainer.bm.logProbability(vector1)));
    System.out.println(Math.exp(trainer.bm.logProbability(vector2)));
    System.out.println(Math.exp(trainer.bm.logProbability(vector3)));
}