@article {pub2735,
	title = {Efficient Rejection Strategies for Prototype-based Classification},
	author = {Lydia Fischer AND Barbara Hammer AND Heiko Wersing},
	year = {2015},
	abstract = {We present simple, efficient reject options for prototype-based classification, evaluated on artificial and benchmark data sets using the example of learning vector quantization. We demonstrate that the reject options improve the accuracy in most cases, and that the performance of the proposed strategies is comparable to the optimal reject option of the Bayes classifier in cases where the latter is available. We show that the results have a comparable performance with a well established reject option for support vector machines and even provide better results in some cases. },
	publisher = {Neurocomputing},
	journal = {Neurocomputing},
	volume = {169},
	pages = {334{\textendash}342}
}