Dynamic Oscillating Search Algorithm for Feature Selection

被引：0

作者：

Somol, P. ^{[1
]}

Novovicova, J. ^{[1
]}

Grim, J. ^{[1
]}

Pudil, P. ^{[2
]}

机构：

[1] Acad Sci Czech Republ, Dept Pattern Recognit, Inst Informat Theory & Automat, Pod Vodarenskou Vezi 4, CZ-18208 Prague 8, Czech Republic

[2] Prague Univ Econom, Fac Management, CZ-37701 Prague, Czech Republic

来源：

19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 | 2008年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce a new feature selection method suitable for non-monotonic criteria, i.e., for Wrapper-based feature selection. Inspired by Oscillating Search, the Dynamic Oscillating Search: (i) is deterministic, (ii) optimizes subset size, (iii) has built-in preference of smaller subsets, (iv) has higher optimization performance than other sequential methods. We show that the new algorithm is capable of over-performing older methods not only in criterion maximization ability but in some cases also in obtaining subsets that generalize better

引用

页码：2308 / 2311

页数：4

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