Title :
Meta analysis of classification algorithms for pattern recognition
Author_Institution :
Dept. of Comput. Sci. & Ind. Syst. Eng., Yonsei Univ., Seoul, South Korea
fDate :
11/1/1999 12:00:00 AM
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;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
