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For research to go in the right direction, it is essential to be able to compare and quantify performance of different algorithms focused on the same problem.
The det curve in assessment of detection task performance
A. Martin, G. Doddington, T. Kamm, M. Ordowski, and M. Przybocki · 1997
Earlier work this paper cites.
Data mining for imbalanced datasets: An overview
Nitesh V Chawla · 2009
Earlier work this paper cites.
Learning from imbalanced data
Haibo He and Edwardo A Garcia · 2009
Earlier work this paper cites.
An empirical comparison of botnet detection methods
Sebastian Garcia, Martin Grill, Jan Stiborek, and Alejandro Zunino · 2014
Cited alongside, same era.
Anonymous article
Anonymous Author(s) · 2017
Cited alongside, same era.
Anonymous article
Anonymous Author(s) · 2017
Cited alongside, same era.
Anonymous article
Anonymous Author(s) · 2017
Later among the works it cites.
Learning from class-imbalanced data: Review of methods and applications
Guo Haixiang et al · 2017
Later among the works it cites.
Deep neural network embeddings for text-independent speaker verification
David Snyder, Daniel Garcia-Romero, Daniel Povey, and Sanjeev Khudanpur · 2017
Later among the works it cites.
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