1 files changed, 74 insertions, 0 deletions
diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/FirstKInitialMeans.java b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/FirstKInitialMeans.java
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+package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2012
+ 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 java.util.ArrayList;
+import java.util.Iterator;
+import java.util.List;
+
+import de.lmu.ifi.dbs.elki.data.NumberVector;
+import de.lmu.ifi.dbs.elki.database.ids.DBID;
+import de.lmu.ifi.dbs.elki.database.relation.Relation;
+import de.lmu.ifi.dbs.elki.distance.distancefunction.PrimitiveDistanceFunction;
+import de.lmu.ifi.dbs.elki.math.linearalgebra.Vector;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+
+/**
+ * Initialize K-means by using the first k objects as initial means.
+ * 
+ * @author Erich Schubert
+ * 
+ * @param <V> Vector type
+ */
+public class FirstKInitialMeans<V extends NumberVector<V, ?>> extends AbstractKMeansInitialization<V> {
+  /**
+   * Constructor.
+   */
+  public FirstKInitialMeans() {
+    super(null);
+  }
+
+  @Override
+  public List<Vector> chooseInitialMeans(Relation<V> relation, int k, PrimitiveDistanceFunction<? super V, ?> distanceFunction) {
+    Iterator<DBID> iter = relation.iterDBIDs();
+    List<Vector> means = new ArrayList<Vector>(k);
+    for(int i = 0; i < k && iter.hasNext(); i++) {
+      means.add(relation.get(iter.next()).getColumnVector());
+    }
+    return means;
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   */
+  public static class Parameterizer<V extends NumberVector<V, ?>> extends AbstractParameterizer {
+    @Override
+    protected FirstKInitialMeans<V> makeInstance() {
+      return new FirstKInitialMeans<V>();
+    }
+  }
+}
+\ No newline at end of file