/*
* Copyright 2010 Ted Dunning. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without modification, are
* permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this list of
* conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright notice, this list
* of conditions and the following disclaimer in the documentation and/or other materials
* provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY <COPYRIGHT HOLDER> ``AS IS'' AND ANY EXPRESS OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
* ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
* NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
* ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
* The views and conclusions contained in the software and documentation are those of the
* authors and should not be interpreted as representing official policies, either expressed
* or implied, of <copyright holder>.
*/
package mia.classifier.ch16;
import org.apache.mahout.math.Vector;
import java.util.Random;
/**
* Encodes a categorical feature.
*/
public class CategoryFeatureEncoder {
private static Random seedGenerator = new Random();
private int probes = 2;
private long seed;
public CategoryFeatureEncoder(String name) {
seed = seedGenerator.nextLong() + name.hashCode();
}
public void addToVector(int category, double weight, Vector data) {
Random hash = new Random(seed + category);
int n = data.size();
for (int i = 0; i < probes; i++) {
int j = hash.nextInt(n);
data.setQuick(j, data.getQuick(j) + weight);
}
}
/**
* Provides the unique hash for a particular probe. For all encoders except text, this is all
* that is needed and the default implementation of hashesForProbe will do the right thing. For
* text and similar values, hashesForProbe should be over-ridden and this method should not be
* used.
*
* @param category original category
* @param probe which probe
* @return The hashes for the given probe
*/
public long hashForProbe(int category, int probe) {
Random hash = new Random(seed + category);
long r = hash.nextLong();
for (int i = 0; i < probe; i++) {
r = hash.nextLong();
}
return r;
}
public void addToVector(int category, Vector data) {
addToVector(category, 1, data);
}
}