| dc.creator |
Koloseni, David |
|
| dc.creator |
Fedrizzi, Mario |
|
| dc.creator |
Luukka, Pasi |
|
| dc.creator |
Lampinen, Jouni |
|
| dc.creator |
Collan, Mikael |
|
| dc.date |
2016-09-21T14:26:02Z |
|
| dc.date |
2016-09-21T14:26:02Z |
|
| dc.date |
2015 |
|
| dc.date.accessioned |
2018-03-27T08:58:14Z |
|
| dc.date.available |
2018-03-27T08:58:14Z |
|
| dc.identifier |
Koloseni, D., Fedrizzi, M., Luukka, P., Lampinen, J. and Collan, M., 2015. Differential Evolution Classifier with Optimized OWA-Based Multi-distance Measures for the Features in the Data Sets. In Intelligent Systems' 2014 (pp. 765-777). Springer International Publishing. |
|
| dc.identifier |
http://hdl.handle.net/20.500.11810/4039 |
|
| dc.identifier |
10.1007/978-3-319-11313-5_67 |
|
| dc.identifier.uri |
http://hdl.handle.net/20.500.11810/4039 |
|
| dc.description |
Full text can be accessed at
http://link.springer.com/chapter/10.1007/978-3-319-11313-5_67 |
|
| dc.description |
This paper introduces a new classification method that uses the differential evolution algorithm to feature-wise select, from a pool of distance measures, an optimal distance measure to be used for classification of elements. The distances yielded for each feature by the optimized distance measures are aggregated into an overall distance vector for each element by using OWA based multi-distance aggregation. |
|
| dc.language |
en |
|
| dc.publisher |
Springer |
|
| dc.subject |
Classification |
|
| dc.subject |
Differential evolution |
|
| dc.subject |
Pool of distances |
|
| dc.subject |
Multi-distances |
|
| dc.title |
Differential Evolution Classifier with Optimized OWA-Based Multi-distance Measures for the Features in the Data Sets |
|
| dc.type |
Book chapter |
|