Application of Estimation of Distribution Algorithm for Feature Selection

被引：1

作者：

Ayodele, Mayowa ^{[1
]}

机构：

[1] Univ Manchester, Manchester, Lancs, England

来源：

PROCEEDINGS OF THE 2019 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION (GECCCO'19 COMPANION) | 2019年

关键词：

Feature Selection; Support Vector Machine; Estimation of Distribution Algorithm;

D O I：

10.1145/3319619.3326771

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Feature selection is a machine learning concept that entails selecting relevant features while eliminating irrelevant and redundant features. This process helps to speed up learning. In this paper, an Estimation of Distribution Algorithm (EDA) is applied to a feature selection problem originating from a legal business. The EDA was able to generate a realistic solution to the real-world problem.

引用

页码：43 / 44

页数：2

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[2]

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[3]

Ayodele Mayowa, 2018, EFFECTIVE EFFCIENT E

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