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- W10367256 abstract "Support Vector Machines (SVM) have demonstrated their ability in solving classiflcation problems in an optimal way with a solid mathematical background. In this paper we improve the interpretability of SVM’s by showing that every SVM is exactly represented by a Fuzzy Rule BasedSystem, for every kernel function used. Nevertheless, this system is in some way compact in their rules and for that reason, we introduce another FRBS, called ‐-FRBS, that approximates it and which is suitable to decompose its rules in simple fuzzy propositions. We show it with an example in the last section." @default.
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- W10367256 date "2005-01-01" @default.
- W10367256 modified "2023-09-23" @default.
- W10367256 title "Interpretation of Support Vector Machines by means of Fuzzy Rule-Based Systems" @default.
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