DocumentCode
1109541
Title
A Comparison of Seven Techniques for Choosing Subsets of Pattern Recognition Properties
Author
Mucciardi, Anthony N. ; Gose, Earl E.
Author_Institution
IEEE
Issue
9
fYear
1971
Firstpage
1023
Lastpage
1031
Abstract
The only guaranteed technique for choosing the best subset of N properties from a set of M is to try all (MN) possible combinations. This is computationally impractical for sets of even moderate size, so heuristic techniques are required. This paper presents seven techniques for choosing good subsets of properties and compares their performance on a nine-class vectorcardiogram classification problem.
Keywords
Classification techniques, dimensionality reduction, electrocardiogram classification, feature extraction, Karhunen-Loéve expansion, multivariate data analysis, pattern recognition, principal components, property selection, statistical decision making.; Biomedical engineering; Data analysis; Decision making; Error analysis; Feature extraction; Military computing; Pattern classification; Pattern recognition; Physiology; Principal component analysis; Classification techniques, dimensionality reduction, electrocardiogram classification, feature extraction, Karhunen-Loéve expansion, multivariate data analysis, pattern recognition, principal components, property selection, statistical decision making.;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/T-C.1971.223398
Filename
1671991
Link To Document