| 基于蚁群算法的分类规则挖掘 |
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| 引用本文： | 蒋蕾,王士同.基于蚁群算法的分类规则挖掘[J].江南大学学报(自然科学版),2008,7(5). |
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| 作者姓名： | 蒋蕾 王士同 |
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| 作者单位： | 江南大学,信息工程学院,江苏,无锡,214122 |
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| 摘 要： | 在Ant-Miner算法基础上提出了一种利用蚁群算法解决分类规则挖掘的算法(ACR),设计了合理的蚂蚁选择属性及属性分区的概率公式,并对规则质量的衡量等策略进行改进,可以较好地挖掘分类规则.在标准数据集上通过与Ant-Miner算法和经典的基于决策树的C 4.5算法比较,ACR在挖掘分类规则的简单性、正确率上有较好的表现.
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| 关 键 词： | 蚁群算法 分类问题 规则发现 数据挖掘 |
Classification Rule Extraction Based on Ant Colony Algorithm |
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| JIANG Lei,WANG Shi-tong.Classification Rule Extraction Based on Ant Colony Algorithm[J].Journal of Southern Yangtze University:Natural Science Edition,2008,7(5). |
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| Authors: | JIANG Lei WANG Shi-tong |
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| Abstract: | Based on the Ant-Miner algorithm,the paper presents a new algorithm for classification rule mining problem in which ant colony algorithm is used.The algorithm uses reasonable probability formula for ant's attributes and attributes values and employs the strategy for rule quality measurement.Therefore,ACR could better discover the classification rules.Compared with Ant-Miner algorithm and the classical C 4.5 algorithm based on decision tree,the experimental results on several benchmark datasets show that ACR can discover classification rules with better simplicity and quality. |
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| Keywords: | ant colony algorithm classification rule discovering data mining |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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