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SVMstruct Support Vector Machine for Complex Outputs Author: Thorsten Joachims <thorsten@joachims.org> Cornell University Department of Computer Science Version: 3.10 Date: 14.08.2008 Overview SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping using labeled training examples (x1,y1), ..
SVMmulticlass Multi-Class Support Vector Machine Author: Thorsten Joachims <thorsten@joachims.org> Cornell University Department of Computer Science Version: 2.20 Date: 14.08.2008 Overview SVMmulticlass uses the multi-class formulation described in [1], but optimizes it with an algorithm that is very fast in the linear case. For a training set (x1,y1) ... (xn,yn) with labels yi in [1..k], it finds
SVMperf Support Vector Machine for Multivariate Performance Measures Author: Thorsten Joachims <thorsten@joachims.org> Cornell University Department of Computer Science Version: 3.00 Date: 07.09.2009 Overview SVMperf is an implementation of the Support Vector Machine (SVM) formulation for optimizing multivariate performance measures described in [Joachims, 2005]. Furthermore, SVMperf implements th
SVMlight Support Vector Machine Author: Thorsten Joachims <thorsten@joachims.org> Cornell University Department of Computer Science Developed at: University of Dortmund, Informatik, AI-Unit Collaborative Research Center on 'Complexity Reduction in Multivariate Data' (SFB475) Version: 6.02 Date: 14.08.2008 Overview SVMlight is an implementation of Support Vector Machines (SVMs) in C. The main featu
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