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Trainable automatic radial basis Support Vector Classifier by LIBSVM


 A Dataset

 W Mapping: Radial Basis Support Vector Classifier
 KERNEL Untrained mapping, representing the optimised kernel


This routine computes a classifier by LIBSVC using a radial basis kernel  with an optimised standard deviation by REGOPTC. The resulting classifier  W is identical to LIBSVC(A,KERNEL). As the kernel optimisation is based  on internal cross-validation the dataset A should be sufficiently large.  Moreover it is very time-consuming as the kernel optimisation needs  about 100 calls to LIBSVC.

Note that LIBSVC is basically a multi-class classifier. The kernel  is thereby the same for all classes. Use MCLASSC to find a multi-class  classifier composed by two-class classifiers with possibly different  kernels.

See also

mappings, datasets, proxm, libsvc, nulibsvc, regoptc,

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