/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.mahout.clustering;
import org.apache.mahout.math.SequentialAccessSparseVector;
import org.apache.mahout.math.Vector;
/**
* This is a simple maximum likelihood clustering policy, suitable for k-means
* clustering
*
*/
public class KMeansClusteringPolicy implements ClusteringPolicy {
/* (non-Javadoc)
* @see org.apache.mahout.clustering.ClusteringPolicy#select(org.apache.mahout.math.Vector)
*/
@Override
public Vector select(Vector probabilities) {
int maxValueIndex = probabilities.maxValueIndex();
Vector weights = new SequentialAccessSparseVector(probabilities.size());
weights.set(maxValueIndex, 1.0);
return weights;
}
/* (non-Javadoc)
* @see org.apache.mahout.clustering.ClusteringPolicy#update(org.apache.mahout.clustering.ClusterClassifier)
*/
@Override
public void update(ClusterClassifier posterior) {
// nothing to do here
}
}