Fuzzy linear support vector machines

Zhimin Yang, Long Wang, N. Deng
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引用次数: 6

Abstract

The paper focuses on the construction of support vector machines when the outputs of training points are triangle fuzzy numbers. First we transform the fuzzy classification problem to chance constrained programming with fuzzy decision, and solve this programming using fuzzy simulation based evolutionary algorithm. Based on this, we proposed the fuzzy linear support vector machines (FLSVM). It can deal with classification problems with fuzzy information as well. At the end, the definition of fuzzy support vector set is given, which can declare the characters of FLSVM.
模糊线性支持向量机
本文主要研究了当训练点的输出为三角形模糊数时支持向量机的构造。首先将模糊分类问题转化为具有模糊决策的机会约束规划问题,并采用基于模糊仿真的进化算法求解该规划问题。在此基础上,提出了模糊线性支持向量机(FLSVM)。它也可以处理模糊信息的分类问题。最后给出了模糊支持向量集的定义,该定义可以说明FLSVM的特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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