@Priority(Priority.SUPPLEMENTARY - 50) public class ByLabelOrAllInOneClustering extends ByLabelClustering {
@Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAllOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
@Priority(Priority.SUPPLEMENTARY - 50) public class ByLabelOrAllInOneClustering extends ByLabelClustering {
@Priority(Priority.SUPPLEMENTARY - 50) public class TrivialNoOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
@Priority(Priority.RECOMMENDED) public class LinearKernelFunction extends PolynomialKernelFunction {
@Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAllOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
@Priority(Priority.RECOMMENDED) public class LinearKernelFunction extends PolynomialKernelFunction {
@Priority(Priority.SUPPLEMENTARY - 50) public class TrivialNoOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
@Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAverageCoordinateOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
@Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAverageCoordinateOutlier extends AbstractAlgorithm<OutlierResult> implements OutlierAlgorithm {
@Priority(Priority.RECOMMENDED) @Alias("rbf") public class RadialBasisFunctionKernelFunction extends AbstractVectorSimilarityFunction {
@Priority(Priority.RECOMMENDED) @Alias("rbf") public class RadialBasisFunctionKernelFunction extends AbstractVectorSimilarityFunction {
bibkey = "journals/misc/FlorekLPSZ51") @Alias({ "single-link", "single", "slink", "nearest", "nearest-neighbor", "de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.SingleLinkageMethod" }) @Priority(Priority.IMPORTANT) public class SingleLinkage implements Linkage {
@Priority(Priority.SUPPLEMENTARY) public class DummyAlgorithm<O extends NumberVector> extends AbstractAlgorithm<Result> {
bibkey = "journals/kansas/SokalM1902") @Alias({ "wpgma", "WPGMA", "de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.WeightedAverageLinkageMethod" }) @Priority(Priority.DEFAULT - 1) public class WeightedAverageLinkage implements Linkage {
bibkey = "journals/misc/FlorekLPSZ51") @Alias({ "single-link", "single", "slink", "nearest", "nearest-neighbor", "de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.SingleLinkageMethod" }) @Priority(Priority.IMPORTANT) public class SingleLinkage implements Linkage {
@Description("Returns a 'trivial' clustering which just considers all points as noise points.") @Alias("de.lmu.ifi.dbs.elki.algorithm.clustering.TrivialAllNoise") @Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAllNoise extends AbstractAlgorithm<Clustering<Model>> implements ClusteringAlgorithm<Clustering<Model>> {
@Description("Returns a 'tivial' clustering which just considers all points to be one big cluster.") @Alias("de.lmu.ifi.dbs.elki.algorithm.clustering.TrivialAllInOne") @Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAllInOne extends AbstractAlgorithm<Clustering<Model>> implements ClusteringAlgorithm<Clustering<Model>> {
@Description("Returns a 'trivial' clustering which just considers all points as noise points.") @Alias("de.lmu.ifi.dbs.elki.algorithm.clustering.TrivialAllNoise") @Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAllNoise extends AbstractAlgorithm<Clustering<Model>> implements ClusteringAlgorithm<Clustering<Model>> {
@Description("Returns a 'tivial' clustering which just considers all points to be one big cluster.") @Alias("de.lmu.ifi.dbs.elki.algorithm.clustering.TrivialAllInOne") @Priority(Priority.SUPPLEMENTARY - 50) public class TrivialAllInOne extends AbstractAlgorithm<Clustering<Model>> implements ClusteringAlgorithm<Clustering<Model>> {