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The relevance vector machine for regression by M.Tipping
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Implementations as in SparseLib 1.0
See : http://research.microsoft.com/mlp/RVM/relevance.htm
Comments from -gb-:
Note : So far requires centered data !!
Note that if you get an error due to "Bad conditioned Hessian"
its an inherent problem in the implementation. Mostly this implementation
works with rbf and rarely with a linear kernel.
Furthermore if you try to solve a multivariate regression problem the
code automatically recognises and you get a multi_reg(relvm_r) object
back!
Example:
d=gen(toyreg({'o=2','n=3'}))
[r,a]=train(relvm_r(kernel('rbf',1)),d)
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Reference : The Relevance Vector Machine |