/*
* Copyright 2011 Keith Stevens
*
* This file is part of the S-Space package and is covered under the terms and
* conditions therein.
*
* The S-Space package is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License version 2 as published
* by the Free Software Foundation and distributed hereunder to you.
*
* THIS SOFTWARE IS PROVIDED "AS IS" AND NO REPRESENTATIONS OR WARRANTIES,
* EXPRESS OR IMPLIED ARE MADE. BY WAY OF EXAMPLE, BUT NOT LIMITATION, WE MAKE
* NO REPRESENTATIONS OR WARRANTIES OF MERCHANT- ABILITY OR FITNESS FOR ANY
* PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE OR DOCUMENTATION
* WILL NOT INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER
* RIGHTS.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package edu.ucla.sspace.clustering.seeding;
import edu.ucla.sspace.common.Statistics;
import edu.ucla.sspace.matrix.Matrix;
import edu.ucla.sspace.vector.DenseVector;
import edu.ucla.sspace.vector.DoubleVector;
import java.util.BitSet;
/**
* This {@link KMeansSeed} implementation selects data points at random from any
* given data set to serve as the initial centroid seeds.
*
* @author Keith Stevens
*/
public class RandomSeed implements KMeansSeed {
/**
* {@inheritDoc}
*/
public DoubleVector[] chooseSeeds(int numCentroids, Matrix dataPoints) {
DoubleVector[] centers = new DoubleVector[numCentroids];
// In the random chance that there are fewer data points than seeds,
// simply set the data points as the seeds.
if (numCentroids >= dataPoints.rows()) {
for (int i = 0; i < dataPoints.rows(); ++i)
centers[i] = dataPoints.getRowVector(i);
// For any extra slots that do not have a data point, use an empty
// vector, which will have zero similarity with any other data
// point.
for (int i = dataPoints.rows(); i < numCentroids; ++i)
centers[i] = new DenseVector(dataPoints.columns());
return centers;
}
// Select a subset of data points to be the new centroids.
BitSet selectedCentroids = Statistics.randomDistribution(
numCentroids, dataPoints.rows());
// Convert the selection indices into vectors.
for (int c = 0, i = selectedCentroids.nextSetBit(0); i >= 0;
c++, i = selectedCentroids.nextSetBit(i+1))
centers[c] = dataPoints.getRowVector(i);
return centers;
}
}