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不完整Vague决策表中的近似集学习方法
引用本文:马志锋,邢汉承,郑晓妹.不完整Vague决策表中的近似集学习方法[J].计算机研究与发展,2000,37(9):1050-1057.
作者姓名:马志锋  邢汉承  郑晓妹
作者单位:1. 东南大学计算机科学与工程系,南京,210096
2. 南京航空航天大学计算机科学与工程系,南京,210016
摘    要:含糊性和不可分辨性构成了决策表中不确定性的两个不同侧面,Vague集作为当前模糊信息处理中的一个新兴研究课题,它具有强大的表达不精确数据的能力,然而针对它的学习方法却未见报导 ,大多数现有针对Vague集的研究仍集中于对其本身性质的讨论,在介绍Vague集的有关概念的基础上,借鉴了粗糙集中中有关近似集的概念,特别对不ague决策表中的学习机制作了研究,解决了数据描述了不确凿时的学习问题,所给出的两

关 键 词:不完整Vague决策表  机器学习  近似集  人工智能

APPROXIMATIONS BASED MACHINE LEARNING APPROACHES IN INCOMPLETE VAGUE DECISION TABLE
MA Zhi-Feng,XING Han-Cheng,ZHENG Xiao-Mei.APPROXIMATIONS BASED MACHINE LEARNING APPROACHES IN INCOMPLETE VAGUE DECISION TABLE[J].Journal of Computer Research and Development,2000,37(9):1050-1057.
Authors:MA Zhi-Feng  XING Han-Cheng  ZHENG Xiao-Mei
Abstract:The vagueness and indiscernibility constitute two aspects of uncertainty in decision table.With a rapid growth of interest in recent years, vague set theory has become an effective tool to handle inexact data in the fields of fuzzy information processing. However, machine learning approaches aiming at vague sets have not been reported yet. Most of the existing researches on vague sets still focus on discussing their properties. In this paper, some basic notions of vague sets are introduced. And then benefiting from the idea of approximations in rough set theory, a learning mechanism of vague decision table is presented, especially for the incomplete table with unknown values. It has solved the learning problems of inexact data. The proposed algorithms are suitable for decision attribute values with precise and vague data respectively.
Keywords:incomplete vague decision table  machine learning  approximations  uncertainty
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