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Java example source code file (Clusterer.java)

This example Java source code file (Clusterer.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

clusterable, clusterer, convergenceexception, distancemeasure, list, mathillegalargumentexception, util

The Clusterer.java Java example source code

 * 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,
 * See the License for the specific language governing permissions and
 * limitations under the License.
package org.apache.commons.math3.ml.clustering;

import java.util.Collection;
import java.util.List;

import org.apache.commons.math3.exception.ConvergenceException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.ml.distance.DistanceMeasure;

 * Base class for clustering algorithms.
 * @param <T> the type of points that can be clustered
 * @since 3.2
public abstract class Clusterer<T extends Clusterable> {

    /** The distance measure to use. */
    private DistanceMeasure measure;

     * Build a new clusterer with the given {@link DistanceMeasure}.
     * @param measure the distance measure to use
    protected Clusterer(final DistanceMeasure measure) {
        this.measure = measure;

     * Perform a cluster analysis on the given set of {@link Clusterable} instances.
     * @param points the set of {@link Clusterable} instances
     * @return a {@link List} of clusters
     * @throws MathIllegalArgumentException if points are null or the number of
     *   data points is not compatible with this clusterer
     * @throws ConvergenceException if the algorithm has not yet converged after
     *   the maximum number of iterations has been exceeded
    public abstract List<? extends Cluster cluster(Collection points)
            throws MathIllegalArgumentException, ConvergenceException;

     * Returns the {@link DistanceMeasure} instance used by this clusterer.
     * @return the distance measure
    public DistanceMeasure getDistanceMeasure() {
        return measure;

     * Calculates the distance between two {@link Clusterable} instances
     * with the configured {@link DistanceMeasure}.
     * @param p1 the first clusterable
     * @param p2 the second clusterable
     * @return the distance between the two clusterables
    protected double distance(final Clusterable p1, final Clusterable p2) {
        return measure.compute(p1.getPoint(), p2.getPoint());


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