DocumentCode
506891
Title
Importance Degree of Features and Feature Selection
Author
Xiao, Di ; Zhang, Junfeng
Author_Institution
Sch. of Autom. & Electr. Eng., Nanjing Univ. of Technol., Nanjing, China
Volume
1
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
197
Lastpage
201
Abstract
A novel measure, importance degree of features, is proposed to rank the features. And a new filter method is presented to carry out feature selection based on such measure. The monotonic property of this proposed measure can reduce the search space, which results in enhancing learning efficiency. The simulation results indicate the validity of our method.
Keywords
pattern recognition; unsupervised learning; feature filter method; feature importance degree; feature selection; machine learning; monotonic property; search space reduction; Automation; Computational efficiency; Computational modeling; Educational institutions; Electric variables measurement; Extraterrestrial measurements; Filters; Fuzzy systems; Space technology; Support vector machines; Feature Ranking; Feature Selection; Importance Degree of Features;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.625
Filename
5358619
Link To Document