Optimal and Linear F-Measure Classifiers Applied to Non-technical Losses Detection
Fernanda Rodríguez, Matías Di Martino, Juan Pablo Kosut, Fernando Santomauro, Federico Lecumberry, Alicia Fernández
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications : 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, November 9-12, 2015, Proceedings, Lecture Notes in Computer Science, Volume 9423, Springer, , page 83--91 - 2015
Research Group(s): Tratamiento de Imagenes (gti)
Department(s): Procesamiento de Señales
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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.

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» Fernanda Rodríguez
» Matías Di Martino
» Juan Pablo Kosut
» Fernando Santomauro
» Federico Lecumberry
» Alicia Fernández