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/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   * 	Redistributions of source code must retain the above copyright notice,
 * 	this list of conditions and the following disclaimer.
 *
 *   *	Redistributions in binary form must reproduce the above copyright notice,
 * 	this list of conditions and the following disclaimer in the documentation
 * 	and/or other materials provided with the distribution.
 *
 *   *	Neither the name of the University of Southampton nor the names of its
 * 	contributors may be used to endorse or promote products derived from this
 * 	software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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package org.openimaj.ml.classification.cascade;

import org.openimaj.image.objectdetection.haar.StageTreeClassifier;

public class CascadeLearner {
	float maximumFPRPerStage;
	float minimumDRPerStage;
	float targetFPR;

	StageTreeClassifier learn() {
		final float overallFPR = 1.0f;
		final float overallDR = 1.0f;

		float previousFPR = overallFPR;
		final float previousDR = overallDR;
		for (int i = 0; overallFPR > targetFPR; i++) {

			for (int n = 0; overallFPR > maximumFPRPerStage * previousFPR; n++) {
				// perform adaboost step

				// evaluate on validation set (compute overallFPR and overallDR)

				// decrease current stage threshold to achieve overallDR >=
				// minimumDRPerStage*previousDR
				// (recompute overallFPR at the same time)
			}

			previousFPR = overallFPR;
		}

		return null;
	}
}




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