/* * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. */ /* * AggregateableEvaluation.java * Copyright (C) 2011-2012 University of Waikato, Hamilton, New Zealand */ package weka.classifiers; import weka.core.Instances; /** * Subclass of Evaluation that provides a method for aggregating the results * stored in another Evaluation object. Delegates to the actual implementation * in weka.classifiers.evaluation.AggregateableEvaluation. * * @author Mark Hall (mhall{[at]}pentaho{[dot]}com) * @version $Revision: 9320 $ */ public class AggregateableEvaluation extends Evaluation { /** For serialization */ private static final long serialVersionUID = 6850546230173753210L; /** * Constructs a new AggregateableEvaluation object * * @param data the Instances to use * @throws Exception if a problem occurs */ public AggregateableEvaluation(Instances data) throws Exception { super(data); m_delegate = new weka.classifiers.evaluation.AggregateableEvaluation(data); } /** * Constructs a new AggregateableEvaluation object * * @param data the Instances to use * @param costMatrix the cost matrix to use * @throws Exception if a problem occurs */ public AggregateableEvaluation(Instances data, CostMatrix costMatrix) throws Exception { super(data, costMatrix); m_delegate = new weka.classifiers.evaluation.AggregateableEvaluation(data, costMatrix); } /** * Constructs a new AggregateableEvaluation object based on an Evaluation * object * * @param eval the Evaluation object to use */ public AggregateableEvaluation(Evaluation eval) throws Exception { super(eval.getHeader()); m_delegate = new weka.classifiers.evaluation.AggregateableEvaluation( eval.m_delegate); } /** * Adds the statistics encapsulated in the supplied Evaluation object into * this one. Does not perform any checks for compatibility between the * supplied Evaluation object and this one. * * @param evaluation the evaluation object to aggregate */ public void aggregate(Evaluation evaluation) { ((weka.classifiers.evaluation.AggregateableEvaluation) m_delegate) .aggregate(evaluation.m_delegate); } }