Feature subset selection method for AdaBoost training

San Yuan Zhao; Ting Zhi Shen; Chen Sheng Sun; Peng Zhang Liu; Lei Yue

Feature subset selection method for AdaBoost training

San Yuan Zhao^*, Ting Zhi Shen, Chen Sheng Sun, Peng Zhang Liu, Lei Yue

^*此作品的通讯作者

计算机学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

The feature-selection problem in training AdaBoost classifiers is addressed in this paper. A working feature subset is generated by adopting a novel feature subset selection method based on the partial least square (PLS) regression, and then trained and selected from this feature subset in Boosting. The experiments show that the proposed PLS-based feature-selection method outperforms the current feature ranking method and the random sampling method.

源语言	英语
页（从-至）	399-402
页数	4
期刊	Journal of Beijing Institute of Technology (English Edition)
卷	20
期	3
出版状态	已出版 - 9月 2011

其它文件与链接

链接到 Scopus 的出版物

引用此

Zhao, S. Y., Shen, T. Z., Sun, C. S., Liu, P. Z., & Yue, L. (2011). Feature subset selection method for AdaBoost training. Journal of Beijing Institute of Technology (English Edition), 20(3), 399-402.

@article{2a5d2e34b52e4c6d9322ab6127a73692,

title = "Feature subset selection method for AdaBoost training",

abstract = "The feature-selection problem in training AdaBoost classifiers is addressed in this paper. A working feature subset is generated by adopting a novel feature subset selection method based on the partial least square (PLS) regression, and then trained and selected from this feature subset in Boosting. The experiments show that the proposed PLS-based feature-selection method outperforms the current feature ranking method and the random sampling method.",

keywords = "Boosting method, Dimensionality reduction, Feature subset",

author = "Zhao, {San Yuan} and Shen, {Ting Zhi} and Sun, {Chen Sheng} and Liu, {Peng Zhang} and Lei Yue",

year = "2011",

month = sep,

language = "English",

volume = "20",

pages = "399--402",

journal = "Journal of Beijing Institute of Technology (English Edition)",

issn = "1004-0579",

publisher = "Beijing Institute of Technology",

number = "3",

}

TY - JOUR

T1 - Feature subset selection method for AdaBoost training

AU - Zhao, San Yuan

AU - Shen, Ting Zhi

AU - Sun, Chen Sheng

AU - Liu, Peng Zhang

AU - Yue, Lei

PY - 2011/9

Y1 - 2011/9

N2 - The feature-selection problem in training AdaBoost classifiers is addressed in this paper. A working feature subset is generated by adopting a novel feature subset selection method based on the partial least square (PLS) regression, and then trained and selected from this feature subset in Boosting. The experiments show that the proposed PLS-based feature-selection method outperforms the current feature ranking method and the random sampling method.

AB - The feature-selection problem in training AdaBoost classifiers is addressed in this paper. A working feature subset is generated by adopting a novel feature subset selection method based on the partial least square (PLS) regression, and then trained and selected from this feature subset in Boosting. The experiments show that the proposed PLS-based feature-selection method outperforms the current feature ranking method and the random sampling method.

KW - Boosting method

KW - Dimensionality reduction

KW - Feature subset

UR - http://www.scopus.com/inward/record.url?scp=80054837490&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:80054837490

SN - 1004-0579

VL - 20

SP - 399

EP - 402

JO - Journal of Beijing Institute of Technology (English Edition)

JF - Journal of Beijing Institute of Technology (English Edition)

IS - 3

ER -

Feature subset selection method for AdaBoost training

摘要

其它文件与链接

指纹

引用此