@Override public InitializeKMeans_F64 createAlg() { return new InitializeStandard_F64(); } }
seed = new InitializeStandard_F64(); break;
seed = new InitializeStandard_F64(); break;
@Override public ComputeClusters<double[]> createClustersAlg( boolean hint ) { if( hint ) { return new ExpectationMaximizationGmm_F64(1000, 1e-8, seeds); } else { InitializeStandard_F64 kseeds = new InitializeStandard_F64(); StandardKMeans_F64 kmeans = new StandardKMeans_F64(1000,1000,1e-8,kseeds); SeedFromKMeans_F64 seeds = new SeedFromKMeans_F64(kmeans); return new ExpectationMaximizationGmm_F64(1000, 1e-8, seeds); } } }
@Override public ComputeClusters<double[]> createClustersAlg( boolean hint ) { if( hint ) { // assume the first 3 are in different groups for the seeds return new StandardKMeans_F64(1000,1000, 1e-8, new FixedSeeds()); } else { InitializeStandard_F64 seeds = new InitializeStandard_F64(); return new StandardKMeans_F64(1000,1000, 1e-8, seeds ); } }
@Test public void matchPointsToClusters() { StandardKMeans_F64 alg = new StandardKMeans_F64(100,100,1,new InitializeStandard_F64()); alg.init(4, 123); alg.clusters.resize(3); alg.workClusters.resize(3); alg.memberCount.resize(3); alg.clusters.data[0] = new double[]{20,0,0,0}; alg.clusters.data[1] = new double[]{0,20,0,0}; alg.clusters.data[2] = new double[]{0,0,20,0}; List<double[]> points = new ArrayList<double[]>(); points.add( new double[]{20,5,0,0}); points.add( new double[]{25,-4,0,0}); points.add( new double[]{0,0,22,0}); alg.matchPointsToClusters(points); assertEquals(2,alg.memberCount.get(0)); assertEquals(0,alg.memberCount.get(1)); assertEquals(1,alg.memberCount.get(2)); assertEquals(45,alg.workClusters.data[0][0],1e-8); assertEquals(1 ,alg.workClusters.data[0][1],1e-8); assertEquals(0 ,alg.workClusters.data[0][2],1e-8); assertEquals(0 ,alg.workClusters.data[0][3],1e-8); assertEquals(0 ,alg.workClusters.data[1][1],1e-8); assertEquals(22,alg.workClusters.data[2][2],1e-8); }
@Test public void updateClusterCenters() { StandardKMeans_F64 alg = new StandardKMeans_F64(100,100,1,new InitializeStandard_F64()); alg.init(4,123); alg.clusters.resize(3); alg.workClusters.resize(3); alg.memberCount.resize(3); double orig[][] = new double[3][4]; orig[0] = new double[]{10,20,30,20}; orig[1] = new double[]{20,10,30,40}; orig[2] = new double[]{3,9,1,12}; alg.workClusters.data[0] = orig[0].clone(); alg.workClusters.data[1] = orig[1].clone(); alg.workClusters.data[2] = orig[2].clone(); alg.memberCount.data[0] = 10; alg.memberCount.data[1] = 1; alg.memberCount.data[2] = 3; // previous clusters will be near zero alg.updateClusterCenters(); for (int i = 0; i < 4; i++) { assertEquals(alg.clusters.data[0][i],orig[0][i]/10); assertEquals(alg.clusters.data[1][i],orig[1][i]/1); assertEquals(alg.clusters.data[2][i],orig[2][i]/3); } }