4 papers · 1 filter
Robustness Quantification for Discriminative Models: a New Robustness Metric and its Application to Dynamic Classifier Selection
Rodrigo F. L. Lassance, Jasper De Bock
Among the different possible strategies for evaluating the reliability of individual predictions of classifiers, robustness quantification stands out as a method that evaluates how…
Robustness Quantification and Uncertainty Quantification: Comparing Two Methods for Assessing the Reliability of Classifier Predictions
Adrián Detavernier, Jasper De Bock
We consider two approaches for assessing the reliability of the individual predictions of a classifier: Robustness Quantification (RQ) and Uncertainty Quantification (UQ). We expla…
Robustness and uncertainty: two complementary aspects of the reliability of the predictions of a classifier
Adrián Detavernier, Jasper De Bock
We consider two conceptually different approaches for assessing the reliability of the individual predictions of a classifier: Robustness Quantification (RQ) and Uncertainty Quanti…
Robustness quantification: a new method for assessing the reliability of the predictions of a classifier
Adrián Detavernier, Jasper De Bock
Based on existing ideas in the field of imprecise probabilities, we present a new approach for assessing the reliability of the individual predictions of a generative probabilistic…