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

Example 1 with KMeansModel

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

the class KMeansLocalClustererExample method main.

/**
 * Executes example.
 *
 * @param args Command line arguments, none required.
 */
public static void main(String[] args) {
    // IMPL NOTE based on KMeansDistributedClustererTestSingleNode#testClusterizationOnDatasetWithObviousStructure
    System.out.println(">>> K-means local clusterer example started.");
    int ptsCnt = 10000;
    DenseLocalOnHeapMatrix points = new DenseLocalOnHeapMatrix(ptsCnt, 2);
    DatasetWithObviousStructure dataset = new DatasetWithObviousStructure(10000);
    List<Vector> massCenters = dataset.generate(points);
    EuclideanDistance dist = new EuclideanDistance();
    OrderedNodesComparator comp = new OrderedNodesComparator(dataset.centers().values().toArray(new Vector[] {}), dist);
    massCenters.sort(comp);
    KMeansLocalClusterer clusterer = new KMeansLocalClusterer(dist, 100, 1L);
    KMeansModel mdl = clusterer.cluster(points, 4);
    Vector[] resCenters = mdl.centers();
    Arrays.sort(resCenters, comp);
    System.out.println("Mass centers:");
    massCenters.forEach(Tracer::showAscii);
    System.out.println("Cluster centers:");
    Arrays.asList(resCenters).forEach(Tracer::showAscii);
    System.out.println("\n>>> K-means local clusterer example completed.");
}

Example 2 with KMeansModel

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

the class LocalModelsTest method importExportKMeansModelTest.

/**
 */
@Test
public void importExportKMeansModelTest() throws IOException {
    executeModelTest(mdlFilePath -> {
        KMeansModel mdl = getClusterModel();
        Exporter<KMeansModelFormat, String> exporter = new FileExporter<>();
        mdl.saveModel(exporter, mdlFilePath);
        KMeansModelFormat load = exporter.load(mdlFilePath);
        Assert.assertNotNull(load);
        KMeansModel importedMdl = new KMeansModel(load.getCenters(), load.getDistance());
        Assert.assertTrue("", mdl.equals(importedMdl));
        return null;
    });
}