Name
Abstract | ||
|---|---|---|
In this paper, the theoretical foundations of generalised fuzzy Bayesian Network based on Vectorial Centroid defuzzification is introduced. The extension of Bayesian Network takes a broad view by examples labelled by a fuzzy set of attributes, instead of a classical set. Combining fuzzy set theory and Bayesian Network's knowledge allows the use of fuzzy variables or attributes that widely used in various applications in science and engineering. It is so highlights the integration of both knowledge's considers the need of human intuition in data analysis. Through the experimental comparison and analysis on the BUPA-liver disorder dataset, the proposed methodology is then validated theoretically and empirically. |
Year | Venue | Keywords |
|---|---|---|
2015 | PROCEEDINGS OF THE 2015 CONFERENCE OF THE INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY | Centroid defuzzification,Vectorial Centroid,Bayesian Network,Human Intuition |
Field | DocType | Volume |
Data mining,Variable-order Bayesian network,Fuzzy classification,Defuzzification,Fuzzy set operations,Fuzzy logic,Fuzzy set,Bayesian network,Artificial intelligence,Fuzzy number,Mathematics | Conference | 89 |
ISSN | Citations | PageRank |
1951-6851 | 2 | 0.40 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ku Muhammad Naim Ku Khalif | 1 | 5 | 2.13 |
| Alexander E. Gegov | 2 | 47 | 8.47 |