题名

An Effective Classification Approach Based on Fuzzy Set and Multiple Criteria Linear Programming

并列篇名

一种基于模糊集和多准则线性规划的有效的分类方法

DOI

10.6338/JDA.200904_4(2).0007

作者

张志旺(Zhi-Wang Zhang)；石勇(Yong Shi)；田英杰(Ying-Jie Tian)

关键词

数据挖掘 ； 模糊集 ； 多准则线性规划 ； 分类 ； Data Mining ； Fuzzy Set ； Multiple Criteria Linear Programming ； Classification

期刊名称

Journal of Data Analysis

卷期/出版年月

4卷2期（2009 / 04 / 01）

页次

105 - 121

内容语文

英文
中文摘要

本文提出了一种基于模糊集和多准则线性规划新的并且有效的数据分析方法，它可用于解决数据挖掘中的分类问题。首先，我们描述了模糊集和用于分类的多准则线性规划的基本理论；然后，给出一种新的用于解决分类问题的多准则模糊线性规划的方法论和模型，该方法和模型充分地综合和模糊集和多准则线性规划的各自的优点，并同时克服了它们的不足。此外，我们在Windows系统平台并在SAS系统环境中开发并实现了该模型及其算法；最后，通过在信用评分领域中的实证研究，其结论和其他方法的对比分析，我们发现在实际应用中这一分类方法要优于单一的多准则线性规划分类方法和其他传统的分类方法。
英文摘要

This paper puts forward a new and effective approach based on fuzzy set and multiple criteria linear programming (MCLP) for solving classification problems in data mining. Firstly, we describe the basic theories of fuzzy set and MCLP model for classification. Then we provide the methodology and model of the multiple criteria fuzzy linear programming approach for classification, which sufficiently integrate their respective virtues and overcome the adverse factors simultaneously. In addition, we also develop and implement the algorithm in SAS system and Windows platform. Finally, by many experiments in credit scoring and medical diagnosis and prognosis, their conclusions and comparison analysis, we find that this classification approach is better than single MCLP model and other traditional classification methods in practical applications.
主题分类 基礎與應用科學 > 資訊科學
基礎與應用科學 > 統計
社會科學 > 管理學
参考文献
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