DocumentCode
1602645
Title
Experiencing fuzzy exemplar-based classifier systems
Author
Sa Lisboa, F.O.S. ; Nicoletti, Maria Do Carmo ; Ramer, Arthur
Author_Institution
IFSC, Sao Paulo Univ., Brazil
Volume
1
fYear
2003
Firstpage
90
Abstract
The NGE model (implemented by EACH) is an incremental form of inductive learning from examples that generalizes a given training set into hypotheses represented as a set of hyperrectangles in an n-dimensional Euclidean space. The NGE algorithm can be considered a descendent of either NN or KNN algorithms. This paper focuses on a fuzzy version of the NGE algorithm, aiming at comparing its performance with a fuzzy version of the NN algorithm and, of the KNN algorithm.
Keywords
fuzzy logic; generalisation (artificial intelligence); learning by example; pattern classification; fuzzy domains; fuzzy exemplar-based classifier systems; generalization; hyperrectangles; incremental form; inductive learning; n-dimensional Euclidean space; nearest neighbour algorithm; nested generalized exemplar; user-defined number of seeds; Australia; Euclidean distance; Fuzzy systems; Humans; Machine learning; Machine learning algorithms; Neural networks; Psychology;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN
0-7803-7810-5
Type
conf
DOI
10.1109/FUZZ.2003.1209343
Filename
1209343
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