| Metadato | Etiqueta | Valor | Idioma |
|---|---|---|---|
| dc.contributor.author | Autor | Rodríguez, Fernanda | es |
| dc.contributor.author | Autor | Di Martino, Matías | es |
| dc.contributor.author | Autor | Kosut, Juan Pablo | es |
| dc.contributor.author | Autor | Santomauro, Fernando | es |
| dc.contributor.author | Autor | Lecumberry, Federico | es |
| dc.contributor.author | Autor | Fernández, Alicia | es |
| dc.date.accessioned | Fecha ingreso | 2024-02-26T19:52:37Z | - |
| dc.date.available | Fecha disponible | 2024-02-26T19:52:37Z | - |
| dc.date.issued | Año de publicación | 2015 | es |
| dc.date.submitted | Fecha de subida | 20240223 | es |
| dc.description.abstract | Resumen | Non-technical loss detection represents a very high cost to power supply companies. Finding classifiers that can deal with this problem is not easy as they have to face a high imbalance scenario with noisy data. In this paper we propose to use Optimal F-measure Classifier (OFC) and Linear F-measure Classifier (LFC), two novel algorithms that are designed to work in problems with unbalanced classes. We compare both algorithm performances with other previously used methods to solve automatic fraud detection problem. | es |
| dc.identifier.citation | Citación | Rodriguez, F., Di Martino, M., Kosut, J.P., Santomauro, F., Lecumberry, F., Fernández, A "Optimal and linear f-measure classifiers applied to non-technical losses detection". Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Scienc, vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_11 | es |
| dc.identifier.doi | DOI | 10.1007/978-3-319-25751-8 11 | es |
| dc.identifier.uri | URI | https://hdl.handle.net/20.500.12008/42684 | - |
| dc.language | metadata.dc.language | en | es |
| dc.publisher | Editorial | Springer International Publishing | es |
| dc.relation.ispartof | EN | 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, 9-12 nov, 2015 | es |
| dc.rights | Derechos | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
| dc.rights.licence | Licencia | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
| dc.subject | Palabras clave | Class imbalance | es |
| dc.subject | Palabras clave | One class SVM | es |
| dc.subject | Palabras clave | F-measure | es |
| dc.subject | Palabras clave | Fraud detection | es |
| dc.subject | Palabras clave | Level set method | es |
| dc.subject.other | Descriptores | Procesamiento de Señales | es |
| dc.title | Título | Optimal and linear F-measure classifiers applied to non-technical losses detection | es |
| dc.type | Tipo de documento | Ponencia | es |
| udelar.academic.department | Departamento académico | Procesamiento de Señales | - |
| udelar.investigation.group | Grupo de investigación | Tratamiento de Imágenes | - |
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| RDKSLF15.pdf | — | 196.99 KB | Adobe PDF |