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Algorithms and components for machine learning and statistics.

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/*
 * File:                SupervisedLearnerValidationExperiment.java
 * Authors:             Justin Basilico
 * Company:             Sandia National Laboratories
 * Project:             Cognitive Foundry
 * 
 * Copyright December 18, 2007, Sandia Corporation.
 * Under the terms of Contract DE-AC04-94AL85000, there is a non-exclusive 
 * license for use of this work by or on behalf of the U.S. Government. Export 
 * of this program may require a license from the United States Government. 
 * See CopyrightHistory.txt for complete details.
 *
 * 
 */

package gov.sandia.cognition.learning.experiment;

import gov.sandia.cognition.evaluator.Evaluator;
import gov.sandia.cognition.learning.data.InputOutputPair;
import gov.sandia.cognition.learning.performance.PerformanceEvaluator;
import gov.sandia.cognition.util.Summarizer;
import java.util.Collection;

/**
 * The {@code SupervisedLearnerValidationExperiment} class extends the
 * {@code LearnerValidationExperiment} class to provide a easy way to create
 * a learner validation experiment for supervised learning.
 * 
 * @param    The type of the input data for supervised learning.
 * @param    The type of the output data for supervised learning.
 * @param    The type of the statistic generated by the 
 *          performance evaluator on the learned object for each fold. It is
 *          created by passing the learned object plus the test data for the
 *          fold into the performance evaluator.
 * @param    The type produced by the summarizer at the end of
 *          the experiment from a collection of the given statistics (one for
 *          each fold). This represents the performance result for the learning
 *          algorithm for the whole experiment.
 * @author  Justin Basilico
 * @since   2.0
 */
public class SupervisedLearnerValidationExperiment
    extends LearnerValidationExperiment, InputOutputPair, Evaluator, StatisticType, SummaryType>
{

    /**
     * Creates a new instance of {@code SupervisedLearnerValidationExperiment}.
     */
    public SupervisedLearnerValidationExperiment()
    {
        this(null, null, null);
    }

    /**
     * Creates a new instance of {@code SupervisedLearnerValidationExperiment}.
     * 
     * @param  foldCreator The object to use for creating the folds.
     * @param  performanceEvaluator The evaluator to use to compute the 
     *         performance of the learned object on each fold.
     * @param  summarizer The summarizer for summarizing the result of the 
     *         performance evaluator from all the folds.
     */
    public SupervisedLearnerValidationExperiment(
        final ValidationFoldCreator, InputOutputPair> foldCreator,
        final PerformanceEvaluator, ? super Collection>, ? extends StatisticType> performanceEvaluator,
        final Summarizer summarizer)
    {
        super(foldCreator, performanceEvaluator, summarizer);
    }

}