Evaluation of feature selection methods for improved EEG classification

被引：0

作者：

AlSukker, Akrarn ^{[1
]}

Al-Ani, Ahmed ^{[1
]}

机构：

[1] Univ Technol Sydney, Fac Engn, Sydney, NSW 2007, Australia

来源：

2006 INTERNATIONAL CONFERENCE ON BIOMEDICAL AND PHARMACEUTICAL ENGINEERING, VOLS 1 AND 2 | 2006年

关键词：

D O I：

暂无

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

This paper compares several methods for feature selection used in EEG classification. Sequential, heuristics and population-based search methods are compared according to their efficiency and computational cost. A support vector machine classifier has been used to compare accuracies. Effect of the size of feature space has been explored by changing the total number of variables between 27 and 168. Experiments have been conducted to select channels as well as to select individual features from different channels.

引用

页码：146 / +

页数：2

共 14 条

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