Feature Selection Using Tabu Search with Learning Memory: Learning Tabu Search

被引：7

作者：

Mousin, Lucien ^{[1
]}

Jourdan, Laetitia ^{[1
]}

Marmion, Marie-Eleonore Kessaci ^{[1
]}

Dhaenens, Clarisse ^{[1
]}

机构：

[1] Univ Lille, Cent Lille, Ctr Rech Informat Signal & Automat Lille, CRIStAL,UMR 9189,CNRS, F-59655 Lille, France

来源：

LEARNING AND INTELLIGENT OPTIMIZATION (LION 10) | 2016年 / 10079卷

关键词：

CLASSIFICATION;

D O I：

10.1007/978-3-319-50349-3_10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Feature selection in classification can be modeled as a combinatorial optimization problem. One of the main particularities of this problem is the large amount of time that may be needed to evaluate the quality of a subset of features. In this paper, we propose to solve this problem with a tabu search algorithm integrating a learning mechanism. To do so, we adapt to the feature selection problem, a learning tabu search algorithm originally designed for a railway network problem in which the evaluation of a solution is time-consuming. Experiments are conducted and show the benefit of using a learning mechanism to solve hard instances of the literature.

引用

页码：141 / 156

页数：16

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