DocumentCode
1277999
Title
Meta analysis of classification algorithms for pattern recognition
Author
Sohn, So Young
Author_Institution
Dept. of Comput. Sci. & Ind. Syst. Eng., Yonsei Univ., Seoul, South Korea
Volume
21
Issue
11
fYear
1999
fDate
11/1/1999 12:00:00 AM
Firstpage
1137
Lastpage
1144
Abstract
Various classification algorithms became available due to a surge of interdisciplinary research interests in the areas of data mining and knowledge discovery. We develop a statistical meta-model which compares the classification performances of several algorithms in terms of data characteristics. This empirical model is expected to aid decision making processes of finding the best classification tool in the sense of providing the minimum classification error among alternatives
Keywords
data mining; pattern classification; statistical analysis; classification algorithms; data characteristics; decision making processes; knowledge discovery; meta analysis; minimum classification error; pattern recognition; statistical meta-model; Algorithm design and analysis; Classification algorithms; Data mining; Decision making; Inspection; Machine learning; Machine learning algorithms; Pattern analysis; Pattern recognition; Surges;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.809107
Filename
809107
Link To Document