FID 3.5: Overview and experimentation

Cezary Z. Janikow; Eryn R. Cantrell

doi:10.1109/NAFIPS-WConSC.2015.7284155

FID 3.5: Overview and experimentation

Cezary Z. Janikow, Eryn R. Cantrell

University of Missouri-St. Louis

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

Abstract

FID is the original fuzzy decision tree, first introduced almost twenty years ago, that sparked a huge variety of hybrid algorithms merging approximate reasoning, fuzzy systems, and mainstream classification algorithms. With the continued interest, this paper describes a newly released update 3.5. One important new addition is a module that can be used to study the effect of noise and missing values on the performance of any classification system - something not well explored in the literature.

Original language	American English
Journal	North American Fuzzy Information Processing Society
DOIs	https://doi.org/10.1109/NAFIPS-WConSC.2015.7284155
State	Published - Aug 1 2015

Keywords

Approximate Reasoning
FID
Fuzzy Decision Trees

Disciplines

Computer Sciences
Artificial Intelligence and Robotics

Access to Document

10.1109/NAFIPS-WConSC.2015.7284155License: Unspecified

Cite this

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M3 - Article

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ER -

FID 3.5: Overview and experimentation

Abstract

Keywords

Disciplines

Access to Document

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