| package com.yahoo.labs.samoa.moa.classifiers.core.splitcriteria; |
| |
| /* |
| * #%L |
| * SAMOA |
| * %% |
| * Copyright (C) 2012 University of Waikato, Hamilton, New Zealand |
| * %% |
| * Licensed 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. |
| * #L% |
| */ |
| |
| import com.yahoo.labs.samoa.moa.core.Utils; |
| |
| /** |
| * Class for computing splitting criteria using information gain with respect to distributions of class values for |
| * Multilabel data. The split criterion is used as a parameter on decision trees and decision stumps. |
| * |
| * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) |
| * @author Jesse Read (jesse@tsc.uc3m.es) |
| * @version $Revision: 1 $ |
| */ |
| public class InfoGainSplitCriterionMultilabel extends InfoGainSplitCriterion { |
| |
| private static final long serialVersionUID = 1L; |
| |
| public static double computeEntropy(double[] dist) { |
| double entropy = 0.0; |
| double sum = 0.0; |
| for (double d : dist) { |
| sum += d; |
| } |
| if (sum > 0.0) { |
| for (double num : dist) { |
| double d = num / sum; |
| if (d > 0.0) { // TODO: how small can d be before log2 overflows? |
| entropy -= d * Utils.log2(d) + (1 - d) * Utils.log2(1 - d); // Extension to Multilabel |
| } |
| } |
| } |
| return sum > 0.0 ? entropy : 0.0; |
| } |
| } |