Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty

R. Senge, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, E. Hüllermeier, Information Sciences 255 (2014) 16–29.

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Journal Article | English
Author
Senge, Robin; Bösner, S.; Dembczynski, K.; Haasenritter, J.; Hirsch, O.; Donner-Banzhoff, N.; Hüllermeier, EykeLibreCat
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Journal Title
Information Sciences
Volume
255
Page
16-29
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Senge R, Bösner S, Dembczynski K, et al. Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty. Information Sciences. 2014;255:16-29.
Senge, R., Bösner, S., Dembczynski, K., Haasenritter, J., Hirsch, O., Donner-Banzhoff, N., & Hüllermeier, E. (2014). Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty. Information Sciences, 255, 16–29.
@article{Senge_Bösner_Dembczynski_Haasenritter_Hirsch_Donner-Banzhoff_Hüllermeier_2014, title={Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty}, volume={255}, journal={Information Sciences}, author={Senge, Robin and Bösner, S. and Dembczynski, K. and Haasenritter, J. and Hirsch, O. and Donner-Banzhoff, N. and Hüllermeier, Eyke}, year={2014}, pages={16–29} }
Senge, Robin, S. Bösner, K. Dembczynski, J. Haasenritter, O. Hirsch, N. Donner-Banzhoff, and Eyke Hüllermeier. “Reliable Classification: Learning Classifiers That Distinguish Aleatoric and Epistemic Uncertainty.” Information Sciences 255 (2014): 16–29.
R. Senge et al., “Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty,” Information Sciences, vol. 255, pp. 16–29, 2014.
Senge, Robin, et al. “Reliable Classification: Learning Classifiers That Distinguish Aleatoric and Epistemic Uncertainty.” Information Sciences, vol. 255, 2014, pp. 16–29.

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