mixKnn: mixKnn
In VBmix: Variational Bayesian Mixture Models

Description Usage Arguments Value Author(s) See Also Examples

performs k-nearest neighbors over a collection of GMM. It uses jsmc to compute distances. Each elements in data is classified against all the others, and inferred class is compared to the true one (leave-one-out).

1	mixKnn(data, labels, n = 2, KLparam = 500)

`data`	list of GMM.
`labels`	vector of numeric labels associated to data.
`n`	k of the algorithm.
`KLparam`	number of samples for jsmc.

classification error ratio in [0,1].

Pierrick Bruneau

mergeClassif constrClassif sampleClassif

temp1 <- sample(1:200, 150)
temp2 <- list()
for(i in temp1) temp2 <- appendToList(temp2, imgmods[[i]])
temp3 <- imglabels[temp1]
# de-activated because this process is very long...
#temp4 <- mixKnn(temp2, temp3)