Abstract
This study analyzes evaluation measures for rare event detection. We introduce a procedure which is built upon the characteristics of rare events. We propose properties for evaluation measures which assess the measure applicability to classification of rare events. Prevention of leaks of personal health information supports the empirical evidence.
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Sokolova, M., El Emam, K., Chowdhury, S., Neri, E., Rose, S., Jonker, E. (2010). Evaluation of Rare Event Detection. In: Farzindar, A., Kešelj, V. (eds) Advances in Artificial Intelligence. Canadian AI 2010. Lecture Notes in Computer Science(), vol 6085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13059-5_51
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DOI: https://doi.org/10.1007/978-3-642-13059-5_51
Publisher Name: Springer, Berlin, Heidelberg
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