基于层次粒化的特征选择算法Feature Selection Algorithm Based on Hierarchical Granulation
陈辉皇,林耀进,王晨曦,童先群,胡敏杰
摘要(Abstract)：
许多实际应用问题中,特征空间存在着层次粒化结构.首先,提出基于核方法度量的层次聚类来对特征空间进行层次粒化.其次,在层次粒化后的各个子空间上,基于邻域互信息考量特征和标记间最大相关以及特征与特征间最小冗余性,在某一指定的层次上对特征进行排序.在此基础上,选择各个子空间具有代表性的部分特征,组成最终的特征子集.最后,在6个UCI数据集和2个不同基分类器上的实验表明所提算法的有效性.
关键词(KeyWords)： 特征选择;粒计算;层次粒化;互信息
基金项目(Foundation): 国家自然科学基金资助项目(61303131,61672272);; 福建省高校新世纪优秀人才、福建省教育厅科技项目(JA14192)
作者(Author): 陈辉皇,林耀进,王晨曦,童先群,胡敏杰
DOI: 10.13705/j.issn.1671-6841.2016096
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