Two hypothetical classifiers compared via DET curves.The same two classifiers compared via traditional ROC curves.
A detection error tradeoff (DET) graph is a graphical plot of error rates for binary classification systems, plotting the false rejection rate vs. false acceptance rate.[1] The x- and y-axes are scaled non-linearly by their standard normal deviates (or just by logarithmic transformation), yielding tradeoff curves that are more linear than ROC curves, and use most of the image area to highlight the differences of importance in the critical operating region.
^A. Martin, A., G. Doddington, T. Kamm, M. Ordowski, and M. Przybocki. "The DET Curve in Assessment of Detection Task Performance", Proc. Eurospeech '97, Rhodes, Greece, September 1997, Vol. 4, pp. 1895-1898.
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