Description Usage Arguments Value Author(s) See Also Examples
performs task analogous to mixKnn (i.e. leave-one-out classification), but uses synthetic representatives to infer labels, instead of k-NN. Each representative is obtained by concatenating all GMM (i.e. elements) of a specific label value, resampling from this redundant mixture, and applying varbayes on this sample.
1 | sampleClassif(data, labels, KLparam = 500, rho = new.env())
|
data |
list of GMM. |
labels |
vector of numeric labels associated to data. |
KLparam |
number of samples for jsmc. |
rho |
R environment object. Used to issue R commands within the C routine. |
classification error ratio in [0,1].
Pierrick Bruneau
mixKnn
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