Examples with KMeansDistributedClusterer org.apache.ignite.ml.clustering.KMeansDistributedClusterer used on opensource projects

Example 1 with KMeansDistributedClusterer

use of org.apache.ignite.ml.clustering.KMeansDistributedClusterer in project ignite by apache.

the class KMeansDistributedClustererExample method main.

/**
 * Executes example.
 *
 * @param args Command line arguments, none required.
 */
public static void main(String[] args) throws InterruptedException {
    // IMPL NOTE based on KMeansDistributedClustererTestSingleNode#testClusterizationOnDatasetWithObviousStructure
    System.out.println(">>> K-means distributed clusterer example started.");
    // Start ignite grid.
    try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
        System.out.println(">>> Ignite grid started.");
        // Create IgniteThread, we must work with SparseDistributedMatrix inside IgniteThread
        // because we create ignite cache internally.
        IgniteThread igniteThread = new IgniteThread(ignite.configuration().getIgniteInstanceName(), SparseDistributedMatrixExample.class.getSimpleName(), () -> {
            int ptsCnt = 10000;
            SparseDistributedMatrix points = new SparseDistributedMatrix(ptsCnt, 2, StorageConstants.ROW_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
            DatasetWithObviousStructure dataset = new DatasetWithObviousStructure(10000);
            List<Vector> massCenters = dataset.generate(points);
            EuclideanDistance dist = new EuclideanDistance();
            KMeansDistributedClusterer clusterer = new KMeansDistributedClusterer(dist, 3, 100, 1L);
            Vector[] resCenters = clusterer.cluster(points, 4).centers();
            System.out.println("Mass centers:");
            massCenters.forEach(Tracer::showAscii);
            System.out.println("Cluster centers:");
            Arrays.asList(resCenters).forEach(Tracer::showAscii);
            points.destroy();
            System.out.println("\n>>> K-means distributed clusterer example completed.");
        });
        igniteThread.start();
        igniteThread.join();
    }
}

Example 2 with KMeansDistributedClusterer

use of org.apache.ignite.ml.clustering.KMeansDistributedClusterer in project ignite by apache.

the class IgniteKMeansDistributedClustererBenchmark method test.

/**
 * {@inheritDoc}
 */
@Override
public boolean test(Map<Object, Object> ctx) throws Exception {
    final DataChanger.Scale scale = new DataChanger.Scale();
    // Create IgniteThread, we must work with SparseDistributedMatrix inside IgniteThread
    // because we create ignite cache internally.
    IgniteThread igniteThread = new IgniteThread(ignite.configuration().getIgniteInstanceName(), this.getClass().getSimpleName(), new Runnable() {

        /**
         * {@inheritDoc}
         */
        @Override
        public void run() {
            // IMPL NOTE originally taken from KMeansDistributedClustererTest
            KMeansDistributedClusterer clusterer = new KMeansDistributedClusterer(new EuclideanDistance(), 1, 1, 1L);
            double[] v1 = scale.mutate(new double[] { 1959, 325100 });
            double[] v2 = scale.mutate(new double[] { 1960, 373200 });
            SparseDistributedMatrix points = new SparseDistributedMatrix(2, 2, StorageConstants.ROW_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
            points.setRow(0, v1);
            points.setRow(1, v2);
            clusterer.cluster(points, 1);
            points.destroy();
        }
    });
    igniteThread.start();
    igniteThread.join();
    return true;
}