mixKnn

Description

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).

Usage

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

Arguments

data

list of GMM.

labels

vector of numeric labels associated to data.

n

k of the algorithm.

KLparam

number of samples for jsmc.

Value

classification error ratio in [0,1].

Author(s)

Pierrick Bruneau

See Also

mergeClassif constrClassif sampleClassif

Examples

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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)

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