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

Example 41 with DenseVector

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

the class VectorNormTest method getDistanceSquaredTest.

/**
 */
@Test
public void getDistanceSquaredTest() {
    consumeSampleVectors((v, desc) -> {
        // IMPL NOTE this initialises vector
        new VectorImplementationsTest.ElementsChecker(v, desc);
        final int size = v.size();
        final Vector vOnHeap = new DenseVector(size);
        invertValues(v, vOnHeap);
        for (int idx = 0; idx < size; idx++) {
            final double exp = v.get(idx);
            final int idxMirror = size - 1 - idx;
            assertTrue("On heap vector difference at " + desc + ", idx " + idx, exp - vOnHeap.get(idxMirror) == 0);
        }
        // IMPL NOTE this won't mutate vOnHeap
        final double exp = vOnHeap.minus(v).getLengthSquared();
        final VectorImplementationsTest.Metric metric = new VectorImplementationsTest.Metric(exp, v.getDistanceSquared(vOnHeap));
        assertTrue("On heap vector not close enough at " + desc + ", " + metric, metric.closeEnough());
    });
}

Example 42 with DenseVector

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

the class EncoderTrainerTest method testFitWithUnknownStringValueInTheGivenData.

/**
 * Tests {@code fit()} method.
 */
@Test
public void testFitWithUnknownStringValueInTheGivenData() {
    Map<Integer, Vector> data = new HashMap<>();
    data.put(1, VectorUtils.of(3.0, 0.0));
    data.put(2, VectorUtils.of(3.0, 12.0));
    data.put(3, VectorUtils.of(3.0, 12.0));
    data.put(4, VectorUtils.of(2.0, 45.0));
    data.put(5, VectorUtils.of(2.0, 45.0));
    data.put(6, VectorUtils.of(14.0, 12.0));
    final Vectorizer<Integer, Vector, Integer, Double> vectorizer = new DummyVectorizer<>(0, 1);
    DatasetBuilder<Integer, Vector> datasetBuilder = new LocalDatasetBuilder<>(data, parts);
    EncoderTrainer<Integer, Vector> strEncoderTrainer = new EncoderTrainer<Integer, Vector>().withEncoderType(EncoderType.STRING_ENCODER).withEncodedFeature(0).withEncodedFeature(1);
    EncoderPreprocessor<Integer, Vector> preprocessor = strEncoderTrainer.fit(TestUtils.testEnvBuilder(), datasetBuilder, vectorizer);
    try {
        preprocessor.apply(7, new DenseVector(new Serializable[] { "Monday", "September" })).features().asArray();
        fail("UnknownCategorialFeatureValue");
    } catch (UnknownCategorialValueException e) {
        return;
    }
    fail("UnknownCategorialFeatureValue");
}

Example 43 with DenseVector

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

the class EncoderTrainerTest method testFitOnStringCategorialFeaturesWithReversedOrder.

/**
 * Tests {@code fit()} method.
 */
@Test
public void testFitOnStringCategorialFeaturesWithReversedOrder() {
    Map<Integer, Vector> data = new HashMap<>();
    data.put(1, new DenseVector(new Serializable[] { "Monday", "September" }));
    data.put(2, new DenseVector(new Serializable[] { "Monday", "August" }));
    data.put(3, new DenseVector(new Serializable[] { "Monday", "August" }));
    data.put(4, new DenseVector(new Serializable[] { "Friday", "June" }));
    data.put(5, new DenseVector(new Serializable[] { "Friday", "June" }));
    data.put(6, new DenseVector(new Serializable[] { "Sunday", "August" }));
    final Vectorizer<Integer, Vector, Integer, Double> vectorizer = new DummyVectorizer<>(0, 1);
    DatasetBuilder<Integer, Vector> datasetBuilder = new LocalDatasetBuilder<>(data, parts);
    EncoderTrainer<Integer, Vector> strEncoderTrainer = new EncoderTrainer<Integer, Vector>().withEncoderType(EncoderType.STRING_ENCODER).withEncoderIndexingStrategy(EncoderSortingStrategy.FREQUENCY_ASC).withEncodedFeature(0).withEncodedFeature(1);
    EncoderPreprocessor<Integer, Vector> preprocessor = strEncoderTrainer.fit(TestUtils.testEnvBuilder(), datasetBuilder, vectorizer);
    assertArrayEquals(new double[] { 2.0, 0.0 }, preprocessor.apply(7, new DenseVector(new Serializable[] { "Monday", "September" })).features().asArray(), 1e-8);
}

Example 44 with DenseVector

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

the class LossFunctionsTest method testMSE.

/**
 */
@Test
public void testMSE() {
    IgniteDifferentiableVectorToDoubleFunction f = LossFunctions.MSE.apply(new DenseVector(new double[] { 2.0, 1.0 }));
    assertNotNull(f);
    test(new double[] { 1.0, 3.0 }, f);
}

Example 45 with DenseVector

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

the class LossFunctionsTest method testHINGE.

/**
 */
@Test
public void testHINGE() {
    IgniteDifferentiableVectorToDoubleFunction f = LossFunctions.HINGE.apply(new DenseVector(new double[] { 2.0, 1.0 }));
    assertNotNull(f);
    test(new double[] { 1.0, 3.0 }, f);
}