Designing decision trees with the use of fuzzy granulation

Designing decision trees with the use of fuzzy granulation

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 cont...

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Veröffentlicht in:IEEE transactions on systems, man and cybernetics. Part A, Systems and humans man and cybernetics. Part A, Systems and humans, 2000-03, Vol.30 (2), p.151-159
Hauptverfasser: Pedrycz, W., Sosnowski, Z.A.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Classification tree analysis
Clustering algorithms
Councils
Data mining
Decision trees
Discretization
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Granulation
Machine learning
Materials handling
Quantization
Standards development
Vehicles
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Zusammenfassung: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.
ISSN:1083-4427
2168-2216
1558-2426
2168-2232
DOI:10.1109/3468.833095