diff options
Diffstat (limited to 'src/de/lmu/ifi/dbs/elki/algorithm/clustering/em/EMClusterModel.java')
-rw-r--r-- | src/de/lmu/ifi/dbs/elki/algorithm/clustering/em/EMClusterModel.java | 81 |
1 files changed, 81 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/em/EMClusterModel.java b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/em/EMClusterModel.java new file mode 100644 index 00000000..f08e6444 --- /dev/null +++ b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/em/EMClusterModel.java @@ -0,0 +1,81 @@ +package de.lmu.ifi.dbs.elki.algorithm.clustering.em; + +/* + This file is part of ELKI: + Environment for Developing KDD-Applications Supported by Index-Structures + + Copyright (C) 2014 + Ludwig-Maximilians-Universität München + Lehr- und Forschungseinheit für Datenbanksysteme + ELKI Development Team + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU Affero General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU Affero General Public License for more details. + + You should have received a copy of the GNU Affero General Public License + along with this program. If not, see <http://www.gnu.org/licenses/>. + */ + +import de.lmu.ifi.dbs.elki.data.NumberVector; +import de.lmu.ifi.dbs.elki.data.model.MeanModel; + +/** + * Models useable in EM clustering. + * + * @author Erich Schubert + */ +public interface EMClusterModel<M extends MeanModel> { + /** + * Begin the E step. + */ + void beginEStep(); + + /** + * Update the + * + * @param vec Vector to process + * @param weight Weight + */ + void updateE(NumberVector vec, double weight); + + /** + * Finalize the E step. + */ + void finalizeEStep(); + + /** + * Estimate the likelihood of a vector. + * + * @param vec Vector + * @return Likelihood. + */ + double estimateDensity(NumberVector vec); + + /** + * Finalize a cluster model. + * + * @return Cluster model + */ + M finalizeCluster(); + + /** + * Get the cluster weight. + * + * @return Cluster weight + */ + double getWeight(); + + /** + * Set the cluster weight. + * + * @param weight Cluster weight + */ + void setWeight(double weight); +}
\ No newline at end of file |