QUANTITATIVE RATING OF THE UNCERTAINTY OF STATEMENTS BY A CLASSIFIER

摘要

A method (100) for rating the uncertainty afflicting the association (3) of measurement data (2) with one or more classes (3a-3c) of a predefined classification by a classifier (1), this classifier (1) comprising at least one artificial neural network, ANN (11), the behaviour of which is characterized by classification parameters (11a), having the steps of: • the measurement data (2), the association (3) ascertained for these measurement data (2) by the classifier (1) and the classification parameters (11a) and architecture (11b) of the ANN (11) are used to ascertain (110) a dependency (4, 4a) of the association (3), and/or a dependency (4, 4b) of a cost function (5) rating the correctness of this association (3), on the classification parameters (11a); • the ascertained dependency (4) is mapped (120) to at least one rating variable (7), which is a measure of the probability p of the association (3) ascertained by the classifier (1) being correct, using at least one trainable rating network (6), the behaviour of which is characterized by rating parameters (6a).