Title :
Classification using small fuzzy biological data sets
Author :
Diederich, Jim ; Fortuner, Renaud
Author_Institution :
Dept. of Math., California Univ., Davis, CA, USA
Abstract :
This paper examines fuzzy methods to identify populations from well-described closely related species. Real nematological data is used to assess the potential and limitations of several methods including one that is introduced to handle large numbers of attributes. Both crisp and fuzzy representations of the data are considered
Keywords :
biology computing; data structures; fuzzy set theory; fuzzy systems; knowledge based systems; learning systems; pattern classification; biological data sets; fuzzy data representations; fuzzy rule based system; fuzzy set theory; nematological data; pattern classification; related species; Doped fiber amplifiers; Functional analysis; Fuzzy sets; Learning systems; Mathematics; Measurement standards; Size measurement; Tail; Testing; Training data;
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4863-X
DOI :
10.1109/FUZZY.1998.686329
