Algoritma Multi-Kelas Twin Bounded SVM Untuk Klasifikasi Pola

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Berny Pebo Tomasouw
Zeth Arthur Leleury

Abstract

Pattern recognition is a process of recognizing patterns by using machine learning algorithm. Pattern recognition can be defined as a classification of data based on knowledge that already gained or  information extracted from patterns. One method that can be used in pattern classification problem is SVM. In this study we introduced Twin Bounded SVM which is refinement of Twin SVM. The discussion begins with the linear Twin Bounded SVM method to solve a two-class classification problem and followed by an algorithm to solve multi-class classification problem

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How to Cite
[1]
B. Tomasouw and Z. Leleury, “Algoritma Multi-Kelas Twin Bounded SVM Untuk Klasifikasi Pola”, Tensor, vol. 1, no. 1, pp. 15-24, May 2020.
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