meka.experiment.evaluationstatistics.InMemory Maven / Gradle / Ivy

Go to download

Show more of this group Show more artifacts with this name
Show all versions of meka Show documentation

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.

The newest version!

/*
 *   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 .
 */

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

package meka.experiment.evaluationstatistics;

import java.util.ArrayList;
import java.util.List;

/**
 * Simple in-memory handler.
 *
 * @author FracPete (fracpete at waikato dot ac dot nz)
 * @version $Revision$
 */
public class InMemory
  extends AbstractEvaluationStatisticsHandler {

	private static final long serialVersionUID = 121028869996940534L;

	/** the collected statistics. */
	protected List m_Statistics = new ArrayList<>();

	/**
	 * Returns whether the handler is threadsafe.
	 *
	 * @return      true if threadsafe
	 */
	@Override
	public boolean isThreadSafe() {
		return true;
	}

	/**
	 * Description to be displayed in the GUI.
	 *
	 * @return      the description
	 */
	public String globalInfo() {
		return "Simply stores the statistics in memory.";
	}

	/**
	 * Initializes the handler.
	 *
	 * @return      null if successfully initialized, otherwise error message
	 */
	@Override
	public String initialize() {
		m_Statistics.clear();
		return null;
	}

	/**
	 * Reads the statistics.
	 *
	 * @return              the statistics that were read
	 */
	@Override
	public List read() {
		return m_Statistics;
	}

	/**
	 * Stores the given statistics.
	 *
	 * @param stats         the statistics to store
	 * @return              null if successfully stored, otherwise error message
	 */
	@Override
	public String write(List stats) {
		m_Statistics.addAll(stats);
		return null;
	}
}