Name
Abstract | ||
|---|---|---|
In this work, we describe the main features of IFS-CoCo, a coevolutionary method performing instance and feature selection for nearest neighbor classifiers. The coevolutionary model and several related background topics are revised, in order to present the method to the ICPR'10 contest "Classifier domains of competence: The Landscape contest". The results obtained show that our proposal is a very competitive approach in the domains considered, outperforming both the benchmark results of the contest and the nearest neighbor rule. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-17711-8_6 | ICPR Contests |
Keywords | Field | DocType |
feature selection,evolutionary algorithms,nearest neighbor | k-nearest neighbors algorithm,Evolutionary algorithm,Feature selection,Pattern recognition,Computer science,Cooperative coevolution,CONTEST,Instance selection,Artificial intelligence,Classifier (linguistics),Machine learning | Conference |
Volume | ISSN | ISBN |
6388 | 0302-9743 | 3-642-17710-7 |
Citations | PageRank | References |
1 | 0.36 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joaquín Derrac | 1 | 2552 | 64.42 |
| Salvador García | 2 | 4151 | 118.45 |
| Francisco Herrera | 3 | 27391 | 1168.49 |