Algoritma Multi-Kelas Twin Bounded SVM Untuk Klasifikasi Pola

B. P. Tomasouw, Z. A. Leleury
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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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多类双额SVM算法分类模式
模式识别是利用机器学习算法对模式进行识别的过程。模式识别可以定义为基于已经获得的知识或从模式中提取的信息对数据进行分类。支持向量机是一种可以用于模式分类问题的方法。本文引入了Twin Bounded SVM,它是对Twin SVM的改进。首先讨论了求解两类分类问题的线性双界支持向量机方法,然后讨论了求解多类分类问题的算法
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