On the quality of neural net classifiers.
This paper describes several concepts and metrics that may be used to assess various aspects of the quality of neural net classifiers. Each concept describes a property that may be taken into account by both designers and users of neural net classifiers when assessing their utility. Besides metrics for assessment of the correctness of classifiers we also introduce metrics that address certain aspects of the misclassifications. We show the applicability of the introduced quality concepts for selection among several neural net classifiers in the domain of thyroid disorders.
Dept. of Medical Informatics, University of Limburg, Maastricht, The Netherlands.
M
M
Egmont-Petersen
J L
JL
Talmon
J
J
Brender
P
P
McNair
D006801:Humans; D016571:Neural Networks, Computer; D011786:Quality Control; D013959:Thyroid Diseases / Q000175:diagnosis