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RBLIBSVC
[W,KERNEL,NU] = RBLIBSVC(A)
Input | |
A | Dataset |
Output | |
W | Mapping: Radial Basis Support Vector Classifier |
KERNEL | Untrained mapping, representing the optimised kernel |
NU | Resulting value for NU from NUSVC |
This routine computes a classifier by NULIBSVC using a radial basis kernel with an optimised standard deviation by REGOPTC. The resulting classifier W is identical to NULIBSVC(A,KERNEL,NU). 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.
mappings, datasets, proxm, libsvc, nulibsvc, regoptc,
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