Title :
Designing decision trees with the use of fuzzy granulation
Author :
Pedrycz, Witold ; Sosnowski, Zenon A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Alberta Univ., Edmonton, Alta., Canada
fDate :
3/1/2000 12:00:00 AM
Abstract :
In this study, we discuss the use of fuzzy sets regarded as a well-rounded algorithmic vehicle in the construction of decision trees. The concept of fuzzy granulation realized via context-based clustering is aimed at the quantization (discretization) of continuous attributes as well as handling continuous classes encountered in classification problems. Two detailed experimental studies are presented concerning well-known data sets available on the Web
Keywords :
decision trees; fuzzy set theory; pattern classification; pattern clustering; WWW; World Wide Web; context-based clustering; continuous attributes; decision tree design; discretization; fuzzy granulation; fuzzy sets; quantization; Classification tree analysis; Clustering algorithms; Councils; Data mining; Decision trees; Fuzzy sets; Machine learning; Quantization; Standards development; Vehicles;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/3468.833095
