In this paper, the error-reject trade-off of linearly combined multiple classifiers is analysed in the framework of the minimum risk theory. Theoretical analysis described in [12,13] is extended for handling reject option and the optimality of the error-reject trade-off is analysed under the assumption of independence among the errors of the individual classifiers. Improvements of the error-rej...

We present prototype-based classification schemes, e. g. learning vector quantization, with cost-function-based and geometrically motivated reject options. We evaluate the reject schemes in experiments on artificial and benchmark data sets. We demonstrate that reject options improve the accuracy of the models in most cases, and that the performance of the proposed schemes is comparable to the o...

$EVWUDFW A reject rule devised for a neural classifier based on the Learning Vector Quantization (LVQ) paradigm is presented. The reject option is carried out adaptively to the specific application domain. It is assumed that a performance function P is defined which, taking into account the requirements of a given application expressed in terms of classification, misclassification and reject co...

In pattern recognition systems, Chow’s rule is commonly used to reach a trade-off between error and reject probabilities. In this paper, we investigate the effects of estimate errors affecting the a posteriori probabilities on the optimality of Chow’s rule. We show that the optimal error-reject tradeoff is not provided by Chow’s rule if the a posteriori probabilities are affected by errors. The...

Background Patients usually undergo repeated X-ray examinations after their initial X-ray radiographs are rejected due to poor image quality. This subjects the patients to excess radiation exposure and extra cost.It is therefore investigating the magnitude and causes of reject is mandatory. This study aimed to assess the reject rate of X-ray films and its economic implication in order to obtain...