Name
Abstract | ||
|---|---|---|
•EF-kNN-IVFS, a new fuzzy nearest neighbor classification algorithm based on interval-valued fuzzy sets and evolutionary algorithms is presented.•Interval-valued fuzzy sets provide a way of representing several configurations for the parameters of fuzzyKNN.•Those configurations are set up in an adaptive way: an evolutionary method (CHC) searches for the best possible configuration according to the training data available.•An extensive experimental study demonstrates the good behavior of EF-kNN-IVFS, when compared with other algorithms of the state of the art. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.ins.2015.09.007 | Information Sciences |
Keywords | Field | DocType |
Fuzzy nearest neighbor,Interval-valued fuzzy sets,Evolutionary algorithms,Supervised learning,Classification | Data mining,Fuzzy classification,Fuzzy set operations,Fuzzy set,Artificial intelligence,Fuzzy number,Neuro-fuzzy,Defuzzification,Fuzzy logic,Algorithm,Membership function,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
329 | C | 0020-0255 |
Citations | PageRank | References |
21 | 0.70 | 28 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joaquín Derrac | 1 | 2552 | 64.42 |
| Francisco Chiclana | 2 | 6350 | 284.13 |
| Salvador García | 3 | 4151 | 118.45 |
| Francisco Herrera | 4 | 27391 | 1168.49 |