DocumentCode
351317
Title
A c-fuzzy means algorithm for prototype induction
Author
Baldwin, J.F. ; Lawry, J.
Author_Institution
Dept. of Eng. Math., Bristol Univ., UK
Volume
1
fYear
2000
fDate
7-10 May 2000
Firstpage
164
Abstract
A c-fuzzy means algorithm is described. The algorithm learns fuzzy prototypes to represent data sets and is based on ideas taken from mass assignment theory. The potential of this approach for both unsupervised and supervised learning is illustrated by its application to a number of benchmark and model problems
Keywords
fuzzy set theory; inference mechanisms; knowledge representation; learning (artificial intelligence); c-fuzzy means algorithm; fuzzy set theory; knowledge representation; mass assignment theory; prototype induction; supervised learning; unsupervised learning; Data mining; Databases; Design engineering; Fuzzy set theory; Fuzzy sets; Machine learning; Mathematics; Predictive models; Probability distribution; Prototypes;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on
Conference_Location
San Antonio, TX
ISSN
1098-7584
Print_ISBN
0-7803-5877-5
Type
conf
DOI
10.1109/FUZZY.2000.838652
Filename
838652
Link To Document