Fuzzy partitioning with FID3.1

Cezary Z. Janikow; Maciej Fajfer

doi:10.1109/NAFIPS.1999.781737

Fuzzy partitioning with FID3.1

Cezary Z. Janikow, Maciej Fajfer

University of Missouri-St. Louis

Research output: Contribution to journal › Article › peer-review

Abstract

FID3.1 builds fuzzy decision trees, with a range of choices for fuzzy operators and inferences. Various FID algorithms are being widely used for dealing with numeric and/or imprecise data, for fuzzy classification or for generating fuzzy rules. FID 3.0 adds a number of new features, the most important being a fuzzy partitioning mechanism - construction of fuzzy sets for continuous variables w/o predefined fuzzy terms. FID3.1 improves the mechanism in a number of ways. This paper describes the partitioning method and presents a few comparative experiments.

Original language	American English
Journal	North American Fuzzy Information Processing Society
DOIs	https://doi.org/10.1109/NAFIPS.1999.781737
State	Published - Jan 1 1999

Disciplines

Mathematics
Artificial Intelligence and Robotics

Access to Document

10.1109/NAFIPS.1999.781737License: Unspecified

Cite this

@article{3dd01ac3244c42d39617204548b4036d,

title = "Fuzzy partitioning with FID3.1",

abstract = " FID3.1 builds fuzzy decision trees, with a range of choices for fuzzy operators and inferences. Various FID algorithms are being widely used for dealing with numeric and/or imprecise data, for fuzzy classification or for generating fuzzy rules. FID 3.0 adds a number of new features, the most important being a fuzzy partitioning mechanism - construction of fuzzy sets for continuous variables w/o predefined fuzzy terms. FID3.1 improves the mechanism in a number of ways. This paper describes the partitioning method and presents a few comparative experiments.",

author = "Janikow, {Cezary Z.} and Maciej Fajfer",

year = "1999",

month = jan,

day = "1",

doi = "10.1109/NAFIPS.1999.781737",

language = "American English",

journal = "North American Fuzzy Information Processing Society",

}

TY - JOUR

T1 - Fuzzy partitioning with FID3.1

AU - Janikow, Cezary Z.

AU - Fajfer, Maciej

PY - 1999/1/1

Y1 - 1999/1/1

N2 - FID3.1 builds fuzzy decision trees, with a range of choices for fuzzy operators and inferences. Various FID algorithms are being widely used for dealing with numeric and/or imprecise data, for fuzzy classification or for generating fuzzy rules. FID 3.0 adds a number of new features, the most important being a fuzzy partitioning mechanism - construction of fuzzy sets for continuous variables w/o predefined fuzzy terms. FID3.1 improves the mechanism in a number of ways. This paper describes the partitioning method and presents a few comparative experiments.

AB - FID3.1 builds fuzzy decision trees, with a range of choices for fuzzy operators and inferences. Various FID algorithms are being widely used for dealing with numeric and/or imprecise data, for fuzzy classification or for generating fuzzy rules. FID 3.0 adds a number of new features, the most important being a fuzzy partitioning mechanism - construction of fuzzy sets for continuous variables w/o predefined fuzzy terms. FID3.1 improves the mechanism in a number of ways. This paper describes the partitioning method and presents a few comparative experiments.

UR - http://www.cs.umsl.edu/~janikow/fid/papers/fid31.nafips99.pdf

U2 - 10.1109/NAFIPS.1999.781737

DO - 10.1109/NAFIPS.1999.781737

M3 - Article

JO - North American Fuzzy Information Processing Society

JF - North American Fuzzy Information Processing Society

ER -

Fuzzy partitioning with FID3.1

Abstract

Disciplines

Access to Document

Other files and links

Cite this