Towards a definition of evaluation criteria for probabilistic classifiers

Authors:
Nahla Ben Amor;Salem Benferhat;Zied Elouedi
Affiliations:
Institut Supérieur de Gestion Tunis, Le Bardo, Tunisie;CRIL – CNRS, Université d'Artois, Lens, Cedex, France;Institut Supérieur de Gestion Tunis, Le Bardo, Tunisie
Venue:
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Year:
2005

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Abstract

This paper deals with the evaluation of ”probabilistic” classifiers, where the results of the classification in not a unique class but a probability distribution over the set of possible classes. Our aim is to propose alternative definitions of the well known percent of correct classification (PCC) for probabilistic classifiers. The evaluation functions are called percent of probabilistic-based correct classification (PPCC). We first propose natural properties that an evaluation function should satisfy. Then, we extend these properties to the case when a semantic distance exists between different classes. An example of an evaluation function based on Euclidean distance is provided.