Paper Info
Title
Enhancing Fingrams to deal with precise fuzzy systems
Abstract
Interpretability is a highly valued capability of fuzzy systems that turns essential when dealing with human interaction. Precise fuzzy modeling prioritizes performance at the cost of harming interpretability. Fuzzy Inference-grams (Fingrams) permit the graphical representation of fuzzy systems facilitating their comprehension, analysis and interpretation at inference level. We enhance Fingrams to better represent and analyze precise fuzzy systems. A specific metric and new representations handle the particularities of such systems. A new visual artifact allows to discover the set of data instances not covered by a given fuzzy system. A novel visual representation allows to study in detail the elements that are involved in the inference of a single data instance. The potentials of the enhanced methodology are sketched by taking the Fuzzy Unordered Rule Induction Algorithm (FURIA) as an illustrative example of precise fuzzy system. For instance, a highly valuable representation is obtained for the stretching mechanism of FURIA, thus facilitating its comprehensibility.
Year
DOI
Venue
2016
10.1016/j.fss.2015.05.019
Fuzzy Sets and Systems
Keywords
Field
DocType
FRBS,LFM,PFM,FURIA,Fingram
Neuro-fuzzy,Defuzzification,Fuzzy classification,Fuzzy set operations,Computer science,Fuzzy logic,Artificial intelligence,Adaptive neuro fuzzy inference system,Fuzzy control system,Fuzzy associative matrix,Machine learning
Journal
Volume
Issue
ISSN
297
C
0165-0114
Citations 
PageRank 
References 
4
0.42
36
Authors
3
Name
Order
Citations
PageRank
David P. Pancho1414.95
José M. Alonso2609.86
Luis Magdalena3108660.49