26 search results - page 1 / 6 » The LCCP for Optimizing Kernel Parameters for SVM |
ICANN
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
ESANN
2004
13 years 6 months ago
2004
The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matr...
ESANN
2007
13 years 6 months ago
2007
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...
PR
2010
13 years 3 months ago
2010
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...
MICCAI
2004
Springer
14 years 5 months ago
2004
Springer
The classification of normal and malginant colon tissue cells is crucial to the diagnosis of colon cancer in humans. Given the right set of feature vectors, Support Vector Machines...