@Test
public void testGaussianClusterClassification() {
ClusterClassifier classifier = newGaussianClassifier();
Vector pdf = classifier.classify(new DenseVector(2));
assertEquals("[0,0]", "[0.212, 0.576, 0.212]", AbstractCluster.formatVector(pdf, null));
pdf = classifier.classify(new DenseVector(2).assign(2));
assertEquals("[2,2]", "[0.952, 0.047, 0.000]", AbstractCluster.formatVector(pdf, null));
}
@Test
public void testSoftClusterClassification() {
ClusterClassifier classifier = newSoftClusterClassifier();
Vector pdf = classifier.classify(new DenseVector(2));
assertEquals("[0,0]", "[0.000, 1.000, 0.000]", AbstractCluster.formatVector(pdf, null));
pdf = classifier.classify(new DenseVector(2).assign(2));
assertEquals("[2,2]", "[0.735, 0.184, 0.082]", AbstractCluster.formatVector(pdf, null));
}
@Test
public void testClusterClassification() {
ClusterClassifier classifier = newClusterClassifier();
Vector pdf = classifier.classify(new DenseVector(2));
assertEquals("[0,0]", "[0.107, 0.787, 0.107]", AbstractCluster.formatVector(pdf, null));
pdf = classifier.classify(new DenseVector(2).assign(2));
assertEquals("[2,2]", "[0.867, 0.117, 0.016]", AbstractCluster.formatVector(pdf, null));
}
@Test
public void testCanopyClassification() {
List<Cluster> models = Lists.newArrayList();
DistanceMeasure measure = new ManhattanDistanceMeasure();
models.add(new Canopy(new DenseVector(2).assign(1), 0, measure));
models.add(new Canopy(new DenseVector(2), 1, measure));
models.add(new Canopy(new DenseVector(2).assign(-1), 2, measure));
ClusterClassifier classifier = new ClusterClassifier(models);
Vector pdf = classifier.classify(new DenseVector(2));
assertEquals("[0,0]", "[0.107, 0.787, 0.107]", AbstractCluster.formatVector(pdf, null));
pdf = classifier.classify(new DenseVector(2).assign(2));
assertEquals("[2,2]", "[0.867, 0.117, 0.016]", AbstractCluster.formatVector(pdf, null));
}
@Test(expected = UnsupportedOperationException.class)
public void testMSCanopyClassification() {
List<Cluster> models = Lists.newArrayList();
DistanceMeasure measure = new ManhattanDistanceMeasure();
models.add(new MeanShiftCanopy(new DenseVector(2).assign(1), 0, measure));
models.add(new MeanShiftCanopy(new DenseVector(2), 1, measure));
models.add(new MeanShiftCanopy(new DenseVector(2).assign(-1), 2, measure));
ClusterClassifier classifier = new ClusterClassifier(models);
classifier.classify(new DenseVector(2));
}