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.
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)