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Package de.citec.tcs.alignment.learning

This module is a custom implementation of the Large Margin Nearest Neighbor classification scheme of Weinberger, Saul, et al.

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Package de.citec.tcs.alignment.learning Description

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
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Copyright (C) 2013-2015 Benjamin Paaßen, Georg Zentgraf, AG Theoretical Computer Science, Centre of Excellence Cognitive Interaction Technology (CITEC), University of Bielefeld, licensed under the AGPL v. 3: http://openresearch.cit-ec.de/projects/tcs . This documentation is licensed under the conditions of CC-BY-SA 4.0: https://creativecommons.org/licenses/by-sa/4.0/