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The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.

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/*
 *   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 .
 */

/**
 * EvaluationStatistics.java
 * Copyright (C) 2015 University of Waikato, Hamilton, NZ
 */

package meka.experiment.evaluationstatistics;

import meka.classifiers.multilabel.MultiLabelClassifier;
import meka.core.OptionUtils;
import meka.core.Result;
import weka.core.Instances;
import weka.core.Utils;

import java.util.HashMap;

/**
 * Stores evaluation statistics.
 *
 * @author FracPete (fracpete at waikato dot ac dot nz)
 * @version $Revision$
 */
public class EvaluationStatistics
  extends HashMap  {
	private static final long serialVersionUID = -1873027591755259927L;

	/** the key for the classifier. */
	public final static String KEY_CLASSIFIER = "Classifier";

	/** the key for the relation. */
	public final static String KEY_RELATION = "Relation";

	/** the classifier. */
	protected MultiLabelClassifier m_Classifier;

	/** the classifier commandline. */
	protected String m_CommandLine;

	/** the relation name. */
	protected String m_Relation;

	/**
	 * Default constructor.
	 */
	public EvaluationStatistics() {
		this(null, (String) null, null);
	}

	/**
	 * Extracts the statistics from the Result object.
	 *
	 * @param classifier    the classifier
	 * @param dataset       the dataset
	 * @param result        the evaluation
	 */
	public EvaluationStatistics(MultiLabelClassifier classifier, Instances dataset, Result result) {
		this(classifier, (dataset != null) ? dataset.relationName() : null, result);
	}

	/**
	 * Extracts the statistics from the Result object.
	 *
	 * @param classifier    the classifier
	 * @param relation      the relation
	 * @param result        the evaluation
	 */
	public EvaluationStatistics(MultiLabelClassifier classifier, String relation, Result result) {
		super();

		m_Classifier  = classifier;
		m_CommandLine = (classifier == null) ? null : OptionUtils.toCommandLine(classifier);
		m_Relation    = relation;

		if (result != null) {
			for (String key : result.vals.keySet()) {
				if (result.vals.get(key) instanceof Number)
					put(key, (Number) result.vals.get(key));
			}
			for (String key : result.availableMetrics()) {
				if (result.getMeasurement(key) instanceof Number)
					put(key, (Number) result.getMeasurement(key));
			}
		}
	}

	/**
	 * Returns the classifier for these statistics.
	 *
	 * @return      the classifier, null if not set
	 */
	public MultiLabelClassifier getClassifier() {
		return m_Classifier;
	}

	/**
	 * Returns the commandline of the classifier for these statistics.
	 *
	 * @return      the classifier commandline, null if not set
	 */
	public String getCommandLine() {
		return m_CommandLine;
	}

	/**
	 * Returns the relation for these statistics.
	 *
	 * @return      the relation, null if not set
	 */
	public String getRelation() {
		return m_Relation;
	}

	/**
	 * Returns the statistics as string.
	 *
	 * @return      the statistics
	 */
	public String toString() {
		StringBuilder result = new StringBuilder();
		result.append("Classifier=").append(Utils.toCommandLine(m_Classifier)).append(",");
		result.append("Relation=").append(m_Relation).append(",");
		result.append(super.toString());
		return result.toString();
	}
}