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This paper discusses structural risk minimization in the setting of classification with a reject option. Binary classification is about classifying observations that take values in an arbitrary feature space X into one of two classes, labelled −1 or +1. A discriminant function f : X → R yields a classifier sgn(f(x)) ∈ {−1,+1} that represents our guess of the label Y of a future observation X an...

This paper extends the accept reject algorithm to allow the pro posal distribution to change at each iteration We rst establish a necessary and su cient condition for this generalized accept reject al gorithm to be valid and then show how the Rao Blackwellization of Casella and Robert can be extended to this setting An impor tant application of these results is to the perfect sampling technique...

There are two mechanisms by which the fetus escapes damage from the maternal immune response during pregnancy. First, the placenta serves as an antigen-bearing immunoabsorbent barrier between the maternal and fetal circulation, so that the mother's humoral immune response to fetal antigens derived from the paternal major histocompatibility complex has no effect on the fetus. Second, the placent...

We analyse optimum reject strategies for prototype-based classifiers and real-valued rejection measures, using the distance of a data point to the closest prototype or probabilistic counterparts. We compare reject schemes with global thresholds, and local thresholds for the Voronoi cells of the classifier. For the latter, we develop a polynomial-time algorithm to compute optimum thresholds base...