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 ...
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Newer Version Available
3.1.0→3.1.1

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Licenses

LicenseURL
The GNU Affero General Public License, Version 3 https://gnu.org/licenses/agpl.html

Developers

NameEmailDev IdRolesOrganization
Benjamin Paaßenbpaassen<at>techfak.uni-bielefeld.deCentre of Excellence - Cognitive Interaction Technology (CITEC), Faculty of Technology, Bielefeld University
Georg ZentgrafCentre of Excellence - Cognitive Interaction Technology (CITEC), Faculty of Technology, Bielefeld University