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This paper presents a linear SVM (Support Vector Machine) Pyramidal Tree (SVMPT) for binary classification tasks. SVMPT is a modified version of SVM based Tree Type Neural Networks (SVMTNN), reported earlier in the literature [1]. Both the algorithms use parameter-less SVM proposed by Mangasarian [2] for learning in each node. While SVMTNN insists on 100 percent training accuracy, linear SVMPT uses...
Linear Support Vector Machines (SVMs) have been used successfully to classify text documents into set of concepts. With the increasing number of linear SVM formulations and decomposition algorithms publicly available, this paper performs a study on their efficiency and efficacy for text categorization tasks. Eight publicly available implementations are investigated in terms of Break Even Point (BEP),...
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