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    • weka.classifiers.meta.multisearch.AbstractEvaluationTask Maven / Gradle / Ivy

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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 .
 */

/**
 * AbstractEvaluationTask.java
 * Copyright (C) 2015-2016 University of Waikato, Hamilton, NZ
 */

package weka.classifiers.meta.multisearch;

import weka.classifiers.meta.MultiSearch;
import weka.core.Instances;
import weka.core.SetupGenerator;
import weka.core.setupgenerator.Point;

/**
 * Helper class for evaluating a setup.
 */
public abstract class AbstractEvaluationTask
  implements Runnable {

  /** the owner. */
  protected MultiSearch m_Owner;

  /** the data to use for training. */
  protected Instances m_Train;

  /** the test set to use (cross-validation if null). */
  protected Instances m_Test;

  /** the setup generator to use. */
  protected SetupGenerator m_Generator;

  /** the setup. */
  protected Point m_Values;

  /** the number of folds for cross-validation. */
  protected int m_Folds;

  /** the type of evaluation. */
  protected int m_Evaluation;

  /**
   * Initializes the task.
   *
   * @param owner		the owning MultiSearch classifier
   * @param train		the training data
   * @param test		the test data, can be null
   * @param generator		the generator to use
   * @param values		the setup values
   * @param folds		the number of cross-validation folds
   * @param eval		the type of evaluation
   */
  public AbstractEvaluationTask(
    MultiSearch owner, Instances train, Instances test,
    SetupGenerator generator, Point values, int folds, int eval) {

    super();

    m_Owner      = owner;
    m_Train      = train;
    m_Test       = test;
    m_Generator  = generator;
    m_Values     = values;
    m_Folds      = folds;
    m_Evaluation = eval;

    if (m_Test != null) {
      String msg = m_Train.equalHeadersMsg(m_Test);
      if (msg != null)
	throw new IllegalArgumentException(msg);
    }
  }

  /**
   * Performs the evaluation.
   *
   * @throws Exception	if evaluation fails
   */
  protected abstract void doRun() throws Exception;

  /**
   * Performs the evaluation.
   */
  public void run() {
    try {
      doRun();
    }
    catch (Exception e) {
      System.err.println("Encountered exception while evaluating classifier, skipping!");
      System.err.println("- Values: " + m_Values);
      e.printStackTrace();
      if (m_Owner.getAlgorithm() instanceof AbstractMultiThreadedSearch)
        ((AbstractMultiThreadedSearch) m_Owner.getAlgorithm()).completedEvaluation(m_Values, false);
    }

    cleanUp();
  }

  /**
   * Cleans up after the task finishes.
   */
  public void cleanUp() {
    // clean up
    m_Owner     = null;
    m_Train     = null;
    m_Test      = null;
    m_Generator = null;
    m_Values    = null;
  }
}
    
    
    
    

    




    
    
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