ssKmeanspp: ssKmeanspp

In Noobivsho/ssClust: GMM for semi-supervised case a-la Mclust

Description

Semi-supervised k-means++ (ss-k-means++ initialiation and Lloyd's algorithm).

Usage

ssKmeanspp(data, k, knownLabels, trueLabels, iter.max=100)

Arguments

data	data
k	number of groups
knownLabels	vector of indices of rows of x whose labels are known
trueLabels	length nrow(x) vector of true labels (only trueLabels[knownLabels] matter)
iter.max	maximum number of LLoyd's iterations

Value

centers	Final centers
cluster	Final cluster assignments

Author(s)

Jordan Yoder

References

http://arxiv.org/abs/1602.00360

Examples

library(ssClust)
data = matrix(runif(20),nrow=10,ncol=2)
knownLabels=c(1,2)
trueLabels=rep(NA,10)
trueLabels[1:2] = c(1,0)

res = ssKmeanspp(data, k=2,
		knownLabels=knownLabels, trueLabels=trueLabels) #note trueLabels are 0-indexed

Noobivsho/ssClust documentation built on Aug. 10, 2019, 5:47 a.m.