An Improved Algorithm for Mining Non-Redundant Interacting Feature Subsets

被引：0
|
作者：
Sha, Chaofeng [1 ]
Gong, Jian [1 ]
Zhou, Aoying [2 ]
机构：
[1] Fudan Univ, Sch Comp Sci, Shanghai, Peoples R China
[2] ECNU, Shanghai Key Lab Trustworthy Comp, Shanghai, Peoples R China
来源：
ADVANCES IN DATA AND WEB MANAGEMENT, PROCEEDINGS | 2009年 / 5446卷
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The application of feature subsets with high order correlation in classification has demonstrates its power in a recent study, where non-redundant interacting feature subsets (NIFS) is defined based on multi-information. Ill this paper, we re-examine the problem of finding NIFSs. We further improve the upper bounds and lower bounds on the correlations, which can be used to significantly prune the search space. The experiments on real datasets demonstrate the efficiency and effectiveness of our approach.
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页码：357 / +
页数：2
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