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/*
 * TCS Alignment Toolbox
 * 
 * Copyright (C) 2013-2015
 * Benjamin Paaßen, Georg Zentgraf
 * AG Theoretical Computer Science
 * Centre of Excellence Cognitive Interaction Technology (CITEC)
 * University of Bielefeld
 * 
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Affero 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 Affero General Public License for more details.
 * 
 * You should have received a copy of the GNU Affero General Public License
 * along with this program.  If not, see .
 */
/**
 * This module is a custom implementation of the Large Margin
 * Nearest Neighbor classification scheme of Weinberger, Saul, et al. (2009).
 * It contains an implementation of the k-nearest neighbor and LMNN classifier
 * as well as (most importantly) gradient calculation schemes on the LMNN
 * cost function given a sequential data set and a user-choice of alignment
 * algorithm. This enables users to learn parameters of the alignment
 * distance in question using a gradient descent on the LMNN cost function.
 *
 * More information on this approach can be found in the Masters Thesis
 * "Adaptive Affine Sequence Alignment Using Algebraic Dynamic Programming"
 *
 * @author Benjamin Paassen - bpaassen(at)techfak.uni-bielefeld.de
 */
package de.citec.tcs.alignment.learning;




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