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Fuzzy Support Vector Machines Explained by Trần Ngọc Lâm is a document available to read on EtoBox.

This document summarizes a research paper that proposes fuzzy support vector machines (FSVMs) to address the problem of unclassifiable regions that can occur when applying conventional support vector machines (SVMs) to multi-class pattern classification problems. The paper first describes how SVMs work for two-class problems and how they are extended to multi-class problems by converting it into multiple two-class problems. It then explains that in the multi-class SVM approach, some data points may be uncla

Author

Trần Ngọc Lâm

Language

EN