Davenport, Mark A.Baraniuk, Richard G.Scott, Clayton D.2007-10-312007-10-312006-05-012006-05-01M. A. Davenport, R. G. Baraniuk and C. D. Scott, "Controlling False Alarms with Support Vector Machines," vol. 5, 2006.https://hdl.handle.net/1911/19832Conference PaperWe study the problem of designing support vector classifiers with respect to a Neyman-Pearson criterion. Specifically, given a user-specified level alpha, 0 < alpha < 1, how can we ensure a false alarm rate no greater than a while minimizing the miss rate? We examine two approaches, one based on shifting the offset of a conventionally trained SVM and the other based on the introduction of class-specific weights. Our contributions include a novel heuristic for improved error estimation and a strategy for efficiently searching the parameter space of the second method. We also provide a characterization of the feasible parameter set of the 2nu-SVM on which the second approach is based. The proposed methods are compared on four benchmark datasets.engparameter spaceImage Processing and Pattern analysisConference paperparameter spacehttp://dx.doi.org/10.1109/ICASSP.2006.1661344