samoa-api/src/main/java/org/apache/samoa/moa/classifiers/core/splitcriteria/InfoGainSplitCriterion.java

/*
 * 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.samoa.moa.classifiers.core.splitcriteria;

import org.apache.samoa.moa.core.ObjectRepository;
import org.apache.samoa.moa.core.Utils;
import org.apache.samoa.moa.options.AbstractOptionHandler;
import org.apache.samoa.moa.tasks.TaskMonitor;

import com.github.javacliparser.FloatOption;

/**
 * Class for computing splitting criteria using information gain with respect to distributions of class values. The
 * split criterion is used as a parameter on decision trees and decision stumps.
 * 
 * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
 * @version $Revision: 7 $
 */
public class InfoGainSplitCriterion extends AbstractOptionHandler implements
    SplitCriterion {

  private static final long serialVersionUID = 1L;

  public FloatOption minBranchFracOption = new FloatOption("minBranchFrac",
      'f',
      "Minimum fraction of weight required down at least two branches.",
      0.01, 0.0, 0.5);

  @Override
  public double getMeritOfSplit(double[] preSplitDist,
      double[][] postSplitDists) {
    if (numSubsetsGreaterThanFrac(postSplitDists, this.minBranchFracOption.getValue()) < 2) {
      return Double.NEGATIVE_INFINITY;
    }
    return computeEntropy(preSplitDist) - computeEntropy(postSplitDists);
  }

  @Override
  public double getRangeOfMerit(double[] preSplitDist) {
    int numClasses = preSplitDist.length > 2 ? preSplitDist.length : 2;
    return Utils.log2(numClasses);
  }

  public static double computeEntropy(double[] dist) {
    double entropy = 0.0;
    double sum = 0.0;
    for (double d : dist) {
      if (d > 0.0) { // TODO: how small can d be before log2 overflows?
        entropy -= d * Utils.log2(d);
        sum += d;
      }
    }
    return sum > 0.0 ? (entropy + sum * Utils.log2(sum)) / sum : 0.0;
  }

  public static double computeEntropy(double[][] dists) {
    double totalWeight = 0.0;
    double[] distWeights = new double[dists.length];
    for (int i = 0; i < dists.length; i++) {
      distWeights[i] = Utils.sum(dists[i]);
      totalWeight += distWeights[i];
    }
    double entropy = 0.0;
    for (int i = 0; i < dists.length; i++) {
      entropy += distWeights[i] * computeEntropy(dists[i]);
    }
    return entropy / totalWeight;
  }

  public static int numSubsetsGreaterThanFrac(double[][] distributions, double minFrac) {
    double totalWeight = 0.0;
    double[] distSums = new double[distributions.length];
    for (int i = 0; i < distSums.length; i++) {
      for (int j = 0; j < distributions[i].length; j++) {
        distSums[i] += distributions[i][j];
      }
      totalWeight += distSums[i];
    }
    int numGreater = 0;
    for (double d : distSums) {
      double frac = d / totalWeight;
      if (frac > minFrac) {
        numGreater++;
      }
    }
    return numGreater;
  }

  @Override
  public void getDescription(StringBuilder sb, int indent) {
    // TODO Auto-generated method stub
  }

  @Override
  protected void prepareForUseImpl(TaskMonitor monitor,
      ObjectRepository repository) {
    // TODO Auto-generated method stub
  }
}