Controlling False Alarms with Support Vector Machines
| dc.citation.bibtexName | inproceedings | en_US |
| dc.citation.conferenceName | IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) | en_US |
| dc.citation.firstpage | V-589 | |
| dc.citation.lastpage | V-592 | |
| dc.citation.location | Toulouse, France | en_US |
| dc.citation.volumeNumber | 5 | en_US |
| dc.contributor.author | Davenport, Mark A. | en_US |
| dc.contributor.author | Baraniuk, Richard G. | en_US |
| dc.contributor.author | Scott, Clayton D. | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T00:41:39Z | |
| dc.date.available | 2007-10-31T00:41:39Z | |
| dc.date.issued | 2006-05-01 | en |
| dc.date.modified | 2006-07-31 | en_US |
| dc.date.note | 2006-07-27 | en_US |
| dc.date.submitted | 2006-05-01 | en_US |
| dc.description | Conference Paper | en_US |
| dc.description.abstract | We 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. | en_US |
| dc.identifier.citation | M. A. Davenport, R. G. Baraniuk and C. D. Scott, "Controlling False Alarms with Support Vector Machines," vol. 5, 2006. | * |
| dc.identifier.doi | http://dx.doi.org/10.1109/ICASSP.2006.1661344 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/19832 | |
| dc.language.iso | eng | en |
| dc.relation.project | http://www.ece.rice.edu/~md/npsvm.php | en_US |
| dc.relation.software | http://www.dsp.rice.edu/software | en_US |
| dc.subject | parameter space | * |
| dc.subject.keyword | parameter space | en_US |
| dc.subject.other | Image Processing and Pattern analysis | en_US |
| dc.title | Controlling False Alarms with Support Vector Machines | en_US |
| dc.type | Conference paper | en_US |
| dc.type.dcmi | Text | en |
| dc.type.dcmi | Text | en_US |
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