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| Título: | Optimal and linear F-measure classifiers applied to non-technical losses detection |
| Autor: | Rodríguez, Fernanda Di Martino, Matías Kosut, Juan Pablo Santomauro, Fernando Lecumberry, Federico Fernández, Alicia |
| Tipo: | Ponencia |
| Palabras clave: | Class imbalance, One class SVM, F-measure, Fraud detection, Level set method |
| Descriptores: | Procesamiento de Señales |
| Fecha de publicación: | 2015 |
| 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. |
| Editorial: | Springer International Publishing |
| EN: | 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, 9-12 nov, 2015 |
| 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 |
| Departamento académico: | Procesamiento de Señales |
| Grupo de investigación: | Tratamiento de Imágenes |
| Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
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|---|---|---|---|---|---|
| RDKSLF15.pdf | 196,99 kB | Adobe PDF | Visualizar/Abrir |
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