Name
Abstract | ||
|---|---|---|
In this paper a methodology for optimizing fuzzy classifiers based on B-splines by evolutionary algorithms is presented. The algorithm proposed maximizes the performance and minimizes the size of the classifier. On a well-known classification problem the algorithm using only part of the features has a recognition rate comparable to an LDA on the total feature space. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/KES.2000.885829 | KES'2000: FOURTH INTERNATIONAL CONFERENCE ON KNOWLEDGE-BASED INTELLIGENT ENGINEERING SYSTEMS & ALLIED TECHNOLOGIES, VOLS 1 AND 2, PROCEEDINGS |
Keywords | Field | DocType |
feature space,fuzzy systems,evolutionary algorithm,spline,b splines,fuzzy sets,data analysis,evolutionary algorithms,data mining,evolutionary computation,fuzzy logic,mathematics | Neuro-fuzzy,Evolutionary algorithm,Defuzzification,Pattern recognition,Fuzzy classification,Fuzzy set operations,Computer science,Fuzzy logic,Evolutionary computation,Artificial intelligence,Fuzzy number,Machine learning | Conference |
Citations | PageRank | References |
5 | 0.56 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adolf Grauel | 1 | 34 | 9.56 |
| Ingo Renners | 2 | 7 | 3.03 |
| Lars A. Ludwig | 3 | 7 | 1.41 |