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一种不均衡数据的改进蚁群分类算法 被引量：1

An Improved Ant-Miner Algorithm for Unbalanced Data
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摘要 针对蚁群挖掘算法(ant colony mining algorithm,ACMA)中的规则评价函数和规则修剪方法,提出一种改进的蚁群挖掘算法(improved ant colony mining algorithm,IACMA),并将其应用于不均衡数据分类.数值实验采用基准数据库中3种典型的不均衡数据,结果表明,改进后的算法能有效提取少数类,提高了不均衡数据整体分类效果. Based on the quality function and pruning method of ant colony mining algorithm（ACMA）,an improved ant colony mining algorithm（IACMA） was proposed and applied to unbalanced data classification.Three datasets from the typical benchmark database were used for the numerical experiment.The simulation results show that the IACMA can better process the minor categories,and improve the overall classification accuracy.
作者 徐淑坦 王朝勇 孙延风
机构地区 吉林大学计算机科学与技术学院 吉林工程技术师范学院应用科学学院
出处 《吉林大学学报（理学版）》 CAS CSCD 北大核心 2011年第4期733-739,共7页 Journal of Jilin University:Science Edition
基金 国家自然科学基金(批准号:10872077)
关键词 不均衡数据分类 蚁群分类算法 蚁群挖掘算法 数据挖掘 规则提取 unbalanced data classification Ant-Miner ant colony mining algorithm data mining rule extraction
分类号 TP18 [自动化与计算机技术—控制理论与控制工程] TP311 [自动化与计算机技术—计算机软件与理论]
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二级参考文献42

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共引文献24

同被引文献42

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吉林大学学报（理学版）
2011年 第4期

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