990 search results - page 64 / 198 » Evolving kernels for support vector machine classification |
164
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CORR
2008
Springer
15 years 4 months ago
2008
Springer
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
153
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CDC
2009
IEEE
15 years 5 months ago
2009
IEEE
Classification problems in critical applications such as health care or security often require very high reliability because of the high costs of errors. In order to achieve this r...
141
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PR
2006
15 years 4 months ago
2006
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
151
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JMLR
2008
15 years 4 months ago
2008
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
112
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ICML
2003
IEEE
16 years 5 months ago
2003
IEEE
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...