| dc.contributor | Universidade Estadual Paulista (UNESP) | |
| dc.creator | Nakamura, Rodrigo Yuji Mizobe | |
| dc.creator | Clayton, Reginaldo Pereira | |
| dc.creator | Papa, João Paulo | |
| dc.creator | Falcão, Alexandre Xavier | |
| dc.date | 2014-05-27T11:26:14Z | |
| dc.date | 2016-10-25T18:35:53Z | |
| dc.date | 2014-05-27T11:26:14Z | |
| dc.date | 2016-10-25T18:35:53Z | |
| dc.date | 2011-12-01 | |
| dc.date.accessioned | 2017-04-06T01:54:42Z | |
| dc.date.available | 2017-04-06T01:54:42Z | |
| dc.identifier | Proceedings - 24th SIBGRAPI Conference on Graphics, Patterns and Images, p. 181-188. | |
| dc.identifier | http://hdl.handle.net/11449/72865 | |
| dc.identifier | http://acervodigital.unesp.br/handle/11449/72865 | |
| dc.identifier | 10.1109/SIBGRAPI.2011.25 | |
| dc.identifier | 2-s2.0-84857188160 | |
| dc.identifier | http://dx.doi.org/10.1109/SIBGRAPI.2011.25 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/893700 | |
| dc.description | Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE. | |
| dc.language | eng | |
| dc.relation | Proceedings - 24th SIBGRAPI Conference on Graphics, Patterns and Images | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Optimum-Path Forest | |
| dc.subject | Pattern Recognition | |
| dc.subject | Supervised classification | |
| dc.subject | Classification system | |
| dc.subject | Forest classifiers | |
| dc.subject | Harmony search | |
| dc.subject | Optimal values | |
| dc.subject | Pruning algorithms | |
| dc.subject | Real time | |
| dc.subject | Search-based algorithms | |
| dc.subject | Training sets | |
| dc.subject | Algorithms | |
| dc.subject | Classification (of information) | |
| dc.subject | Forestry | |
| dc.subject | Pattern recognition | |
| dc.subject | Parameter estimation | |
| dc.subject | Information Retrieval | |
| dc.title | Optimum-Path Forest pruning parameter estimation through Harmony Search | |
| dc.type | Otro | |
