Examples with DenseVector org.apache.ignite.ml.math.primitives.vector.impl.DenseVector used on opensource projects

Example 61 with DenseVector

use of org.apache.ignite.ml.math.primitives.vector.impl.DenseVector in project ignite by apache.

the class SVMModelTest method testPredictWithErasedLabelsAndChangedThreshold.

/**
 */
@Test
public void testPredictWithErasedLabelsAndChangedThreshold() {
    Vector weights = new DenseVector(new double[] { 1.0, 1.0 });
    SVMLinearClassificationModel mdl = new SVMLinearClassificationModel(weights, 1.0).withThreshold(5);
    Vector observation = new DenseVector(new double[] { 1.0, 1.0 });
    TestUtils.assertEquals(0.0, mdl.predict(observation), PRECISION);
    observation = new DenseVector(new double[] { 3.0, 4.0 });
    TestUtils.assertEquals(1.0, mdl.predict(observation), PRECISION);
    TestUtils.assertEquals(5, mdl.threshold(), PRECISION);
}

Example 62 with DenseVector

use of org.apache.ignite.ml.math.primitives.vector.impl.DenseVector in project ignite by apache.

the class SparkModelParser method loadKMeansModel.

/**
 * Load K-Means model.
 *
 * @param pathToMdl Path to model.
 * @param learningEnvironment learningEnvironment
 */
private static Model loadKMeansModel(String pathToMdl, LearningEnvironment learningEnvironment) {
    Vector[] centers = null;
    try (ParquetFileReader r = ParquetFileReader.open(HadoopInputFile.fromPath(new Path(pathToMdl), new Configuration()))) {
        PageReadStore pages;
        final MessageType schema = r.getFooter().getFileMetaData().getSchema();
        final MessageColumnIO colIO = new ColumnIOFactory().getColumnIO(schema);
        while (null != (pages = r.readNextRowGroup())) {
            final int rows = (int) pages.getRowCount();
            final RecordReader recordReader = colIO.getRecordReader(pages, new GroupRecordConverter(schema));
            centers = new DenseVector[rows];
            for (int i = 0; i < rows; i++) {
                final SimpleGroup g = (SimpleGroup) recordReader.read();
                // final int clusterIdx = g.getInteger(0, 0);
                Group clusterCenterCoeff = g.getGroup(1, 0).getGroup(3, 0);
                final int amountOfCoefficients = clusterCenterCoeff.getFieldRepetitionCount(0);
                centers[i] = new DenseVector(amountOfCoefficients);
                for (int j = 0; j < amountOfCoefficients; j++) {
                    double coefficient = clusterCenterCoeff.getGroup(0, j).getDouble(0, 0);
                    centers[i].set(j, coefficient);
                }
            }
        }
    } catch (IOException e) {
        String msg = "Error reading parquet file: " + e.getMessage();
        learningEnvironment.logger().log(MLLogger.VerboseLevel.HIGH, msg);
        e.printStackTrace();
    }
    return new KMeansModel(centers, new EuclideanDistance());
}

Example 63 with DenseVector

use of org.apache.ignite.ml.math.primitives.vector.impl.DenseVector in project ignite by apache.

the class SparkModelParser method readLinRegCoefficients.

/**
 * Read coefficient matrix from parquet.
 *
 * @param g Coefficient group.
 * @return Vector of coefficients.
 */
private static Vector readLinRegCoefficients(SimpleGroup g) {
    Vector coefficients;
    Group coeffGroup = g.getGroup(1, 0).getGroup(3, 0);
    final int amountOfCoefficients = coeffGroup.getFieldRepetitionCount(0);
    coefficients = new DenseVector(amountOfCoefficients);
    for (int j = 0; j < amountOfCoefficients; j++) {
        double coefficient = coeffGroup.getGroup(0, j).getDouble(0, 0);
        coefficients.set(j, coefficient);
    }
    return coefficients;
}

Example 64 with DenseVector

use of org.apache.ignite.ml.math.primitives.vector.impl.DenseVector in project ignite by apache.

the class SparkModelParser method readCoefficients.

/**
 * Read coefficient matrix from parquet.
 *
 * @param g Coefficient group.
 * @return Vector of coefficients.
 */
private static Vector readCoefficients(SimpleGroup g) {
    Vector coefficients;
    final int amountOfCoefficients = g.getGroup(3, 0).getGroup(5, 0).getFieldRepetitionCount(0);
    coefficients = new DenseVector(amountOfCoefficients);
    for (int j = 0; j < amountOfCoefficients; j++) {
        double coefficient = g.getGroup(3, 0).getGroup(5, 0).getGroup(0, j).getDouble(0, 0);
        coefficients.set(j, coefficient);
    }
    return coefficients;
}

Example 65 with DenseVector

use of org.apache.ignite.ml.math.primitives.vector.impl.DenseVector in project ignite by apache.

the class LocalModelsTest method importExportSVMBinaryClassificationModelTest.

/**
 */
@Test
public void importExportSVMBinaryClassificationModelTest() throws IOException {
    executeModelTest(mdlFilePath -> {
        SVMLinearClassificationModel mdl = new SVMLinearClassificationModel(new DenseVector(new double[] { 1, 2 }), 3);
        Exporter<SVMLinearClassificationModel, String> exporter = new FileExporter<>();
        mdl.saveModel(exporter, mdlFilePath);
        SVMLinearClassificationModel load = exporter.load(mdlFilePath);
        Assert.assertNotNull(load);
        Assert.assertEquals("", mdl, load);
        return null;
    });
}