FID3: fuzzy induction decision tree

Author

Rives, Julio

Author_Institution

Area Tecnologica Tratamiento de la Inf., Inisel, Madrid, Spain

fYear

1990

fDate

3-5 Dec 1990

Firstpage

457

Lastpage

462

Abstract

An overview of FID3, a technique of fuzzy learning, is presented. Some basic ideas of uncertainty and information are reviewed. A measure of the dependence degree among the variables involved in a possibility distribution is described which suggests a method to select the most informative attributes of a training base. A measure of the vagueness of fuzzy sets is defined which suggests a new method of simplifying concepts. Finally, the author highlights some FID3 enhancements from which the reader can comprehend its potential advantages

Keywords

decision theory; fuzzy logic; fuzzy set theory; inference mechanisms; learning systems; trees (mathematics); FID3; decision tree; fuzzy induction; fuzzy learning; fuzzy logic; fuzzy set theory; possibility distribution; uncertainty; vagueness; Decision trees; Extrapolation; Fuzzy set theory; Fuzzy sets; Interpolation; Knowledge acquisition; Machine learning; Machine learning algorithms; Possibility theory; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Uncertainty Modeling and Analysis, 1990. Proceedings., First International Symposium on

Conference_Location

College Park, MD

Print_ISBN

0-8186-2107-9

Type

conf

DOI

10.1109/ISUMA.1990.151297

Filename

151297

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2080409