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-rw-r--r--src/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/FourC.java239
1 files changed, 204 insertions, 35 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/FourC.java b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/FourC.java
index 5235273c..c6b18812 100644
--- a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/FourC.java
+++ b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/FourC.java
@@ -4,7 +4,7 @@ package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation;
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
- Copyright (C) 2013
+ Copyright (C) 2014
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
@@ -23,41 +23,53 @@ package de.lmu.ifi.dbs.elki.algorithm.clustering.correlation;
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
-import de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN;
-import de.lmu.ifi.dbs.elki.data.Clustering;
+import de.lmu.ifi.dbs.elki.algorithm.clustering.DBSCAN;
+import de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.FourCCorePredicate;
+import de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.FourCNeighborPredicate;
+import de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN;
import de.lmu.ifi.dbs.elki.data.NumberVector;
-import de.lmu.ifi.dbs.elki.data.model.Model;
import de.lmu.ifi.dbs.elki.data.type.TypeInformation;
import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
-import de.lmu.ifi.dbs.elki.distance.distancefunction.LocallyWeightedDistanceFunction;
-import de.lmu.ifi.dbs.elki.distance.distancevalue.DoubleDistance;
-import de.lmu.ifi.dbs.elki.index.preprocessed.subspaceproj.FourCSubspaceIndex;
import de.lmu.ifi.dbs.elki.logging.Logging;
+import de.lmu.ifi.dbs.elki.math.linearalgebra.pca.LimitEigenPairFilter;
import de.lmu.ifi.dbs.elki.utilities.documentation.Description;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
import de.lmu.ifi.dbs.elki.utilities.documentation.Title;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.constraints.CommonConstraints;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.DoubleParameter;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.Flag;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.IntParameter;
/**
* 4C identifies local subgroups of data objects sharing a uniform correlation.
* The algorithm is based on a combination of PCA and density-based clustering
* (DBSCAN).
+ *
+ * Reference:
* <p>
- * Reference: Christian Böhm, Karin Kailing, Peer Kröger, Arthur Zimek:
+ * C. Böhm, K. Kailing, P. Kröger, A. Zimek:<br />
* Computing Clusters of Correlation Connected Objects. <br>
* In Proc. ACM SIGMOD Int. Conf. on Management of Data, Paris, France, 2004.
* </p>
*
* @author Arthur Zimek
*
- * @apiviz.uses FourCSubspaceIndex
+ * @apiviz.composedOf FourCNeighborPredicate
+ * @apiviz.composedOf FourCCorePredicate
*
* @param <V> type of NumberVector handled by this Algorithm
*/
@Title("4C: Computing Correlation Connected Clusters")
-@Description("4C identifies local subgroups of data objects sharing a uniform correlation. " + "The algorithm is based on a combination of PCA and density-based clustering (DBSCAN).")
-@Reference(authors = "C. Böhm, K. Kailing, P. Kröger, A. Zimek", title = "Computing Clusters of Correlation Connected Objects", booktitle = "Proc. ACM SIGMOD Int. Conf. on Management of Data, Paris, France, 2004, 455-466", url = "http://dx.doi.org/10.1145/1007568.1007620")
-public class FourC<V extends NumberVector<?>> extends AbstractProjectedDBSCAN<Clustering<Model>, V> {
+@Description("4C identifies local subgroups of data objects sharing a uniform correlation. " //
+ + "The algorithm is based on a combination of PCA and density-based clustering (DBSCAN).")
+@Reference(authors = "C. Böhm, K. Kailing, P. Kröger, A. Zimek", //
+title = "Computing Clusters of Correlation Connected Objects", //
+booktitle = "Proc. ACM SIGMOD Int. Conf. on Management of Data, Paris, France, 2004, 455-466", //
+url = "http://dx.doi.org/10.1145/1007568.1007620")
+public class FourC<V extends NumberVector> extends GeneralizedDBSCAN {
/**
* The logger for this class.
*/
@@ -66,23 +78,10 @@ public class FourC<V extends NumberVector<?>> extends AbstractProjectedDBSCAN<Cl
/**
* Constructor.
*
- * @param epsilon Epsilon value
- * @param minpts MinPts value
- * @param distanceFunction Distance function
- * @param lambda Lambda value
+ * @param settings FourC settings.
*/
- public FourC(DoubleDistance epsilon, int minpts, LocallyWeightedDistanceFunction<V> distanceFunction, int lambda) {
- super(epsilon, minpts, distanceFunction, lambda);
- }
-
- @Override
- public String getLongResultName() {
- return "4C Clustering";
- }
-
- @Override
- public String getShortResultName() {
- return "4c-clustering";
+ public FourC(FourC.Settings settings) {
+ super(new FourCNeighborPredicate<V>(settings), new FourCCorePredicate(settings), false);
}
@Override
@@ -96,26 +95,196 @@ public class FourC<V extends NumberVector<?>> extends AbstractProjectedDBSCAN<Cl
}
/**
+ * Class wrapping the 4C parameter settings.
+ *
+ * @author Erich Schubert
+ *
+ * @apiviz.exclude
+ */
+ public static class Settings {
+ /**
+ * Query radius epsilon.
+ */
+ public double epsilon;
+
+ /**
+ * Use absolute variance, not relative variance.
+ */
+ public boolean absolute = false;
+
+ /**
+ * Delta parameter, for selecting strong Eigenvectors.
+ */
+ public double delta = 0.0;
+
+ /**
+ * Kappa penalty parameter, to punish deviation in low-variance
+ * Eigenvectors.
+ */
+ public double kappa = 50.;
+
+ /**
+ * Maximum subspace dimensionality lambda.
+ */
+ public int lambda = Integer.MAX_VALUE;
+
+ /**
+ * MinPts / mu parameter.
+ */
+ public int minpts;
+
+ /**
+ * Parameterization class for 4C settings.
+ *
+ * @author Erich Schubert
+ *
+ * @apiviz.exclude
+ */
+ public static class Parameterizer extends AbstractParameterizer {
+ /**
+ * The default value for delta.
+ */
+ public static final double DEFAULT_DELTA = .1;
+
+ /**
+ * Parameter Kappa: penalty for deviations in preferred dimensions.
+ */
+ public static final OptionID KAPPA_ID = new OptionID("predecon.kappa", "Penalty factor for deviations in preferred (low-variance) dimensions.");
+
+ /**
+ * Default for kappa parameter.
+ */
+ public static final double KAPPA_DEFAULT = 20.;
+
+ /**
+ * Parameter Lambda: maximum dimensionality allowed.
+ */
+ public static final OptionID LAMBDA_ID = new OptionID("predecon.lambda", "Maximum dimensionality to consider for core points.");
+
+ /**
+ * Settings storage.
+ */
+ Settings settings;
+
+ @Override
+ protected void makeOptions(Parameterization config) {
+ settings = new Settings();
+ configEpsilon(config);
+ configMinPts(config);
+ configDelta(config);
+ configKappa(config);
+ configLambda(config);
+ }
+
+ /**
+ * Configure the epsilon radius parameter.
+ *
+ * @param config Parameter source
+ */
+ protected void configEpsilon(Parameterization config) {
+ DoubleParameter epsilonP = new DoubleParameter(DBSCAN.Parameterizer.EPSILON_ID) //
+ .addConstraint(CommonConstraints.GREATER_EQUAL_ZERO_DOUBLE);
+ if(config.grab(epsilonP)) {
+ settings.epsilon = epsilonP.doubleValue();
+ }
+ }
+
+ /**
+ * Configure the minPts aka "mu" parameter.
+ *
+ * @param config Parameter source
+ */
+ protected void configMinPts(Parameterization config) {
+ IntParameter minptsP = new IntParameter(DBSCAN.Parameterizer.MINPTS_ID) //
+ .addConstraint(CommonConstraints.GREATER_EQUAL_ONE_INT);
+ if(config.grab(minptsP)) {
+ settings.minpts = minptsP.intValue();
+ }
+ }
+
+ /**
+ * Configure the delta parameter.
+ *
+ * @param config Parameter source
+ */
+ protected void configDelta(Parameterization config) {
+ // Flag for using absolute variances
+ Flag absoluteF = new Flag(LimitEigenPairFilter.EIGENPAIR_FILTER_ABSOLUTE);
+ if(config.grab(absoluteF)) {
+ settings.absolute = absoluteF.isTrue();
+ }
+
+ // Parameter delta
+ DoubleParameter deltaP = new DoubleParameter(LimitEigenPairFilter.EIGENPAIR_FILTER_DELTA) //
+ .addConstraint(CommonConstraints.GREATER_EQUAL_ZERO_DOUBLE);
+ if(!settings.absolute) {
+ deltaP.setDefaultValue(DEFAULT_DELTA);
+ }
+ else {
+ deltaP.addConstraint(CommonConstraints.LESS_EQUAL_ONE_DOUBLE);
+ }
+ if(config.grab(deltaP)) {
+ settings.delta = deltaP.doubleValue();
+ }
+ }
+
+ /**
+ * Configure the kappa parameter.
+ *
+ * @param config Parameter source
+ */
+ protected void configKappa(Parameterization config) {
+ DoubleParameter kappaP = new DoubleParameter(KAPPA_ID) //
+ .addConstraint(CommonConstraints.GREATER_THAN_ONE_DOUBLE) //
+ .setDefaultValue(KAPPA_DEFAULT);
+ if(config.grab(kappaP)) {
+ settings.kappa = kappaP.doubleValue();
+ }
+ }
+
+ /**
+ * Configure the delta parameter.
+ *
+ * @param config Parameter source
+ */
+ protected void configLambda(Parameterization config) {
+ IntParameter lambdaP = new IntParameter(LAMBDA_ID) //
+ .addConstraint(CommonConstraints.GREATER_EQUAL_ONE_INT) //
+ .setOptional(true);
+ if(config.grab(lambdaP)) {
+ settings.lambda = lambdaP.intValue();
+ }
+ }
+
+ @Override
+ protected Object makeInstance() {
+ return settings;
+ }
+ }
+ }
+
+ /**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
- public static class Parameterizer<O extends NumberVector<?>> extends AbstractProjectedDBSCAN.Parameterizer<O, DoubleDistance> {
+ public static class Parameterizer<O extends NumberVector> extends AbstractParameterizer {
+ /**
+ * Settings storage.
+ */
+ Settings settings;
+
@Override
protected void makeOptions(Parameterization config) {
super.makeOptions(config);
- configInnerDistance(config);
- configEpsilon(config, innerdist);
- configMinPts(config);
- configOuterDistance(config, epsilon, minpts, FourCSubspaceIndex.Factory.class, innerdist);
- configLambda(config);
+ settings = config.tryInstantiate(FourC.Settings.class);
}
@Override
protected FourC<O> makeInstance() {
- return new FourC<>(epsilon, minpts, outerdist, lambda);
+ return new FourC<>(settings);
}
}
} \ No newline at end of file
generated by cgit v1.2.3 (git 2.25.1) at 2024-05-22 01:45:30 +0000