HDclust: clustControl – R documentation

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clustControl

Parameters for MBM clustering algorithm.

Description

This function creates a list with parameters for Modal Baum-Welch (MBW) clustering algorithm used as an argument for hmmvbClust.

Usage

clustControl(minSize = 1, modeTh = 0.01, useL1norm = FALSE,
  getlikelh = FALSE)

Arguments

`minSize`	Minimum cluster size. Clusters that contain the number of data points smaller than `minSize` are merged to the closest big cluster.
`modeTh`	Distance parameter that controls mode merging. Larger values promote merging of different clusters.
`useL1norm`	A logical value indicating whether or not L1 norm will be used to calculate the distance.
`getlikelh`	A logical value indicating whether or not to calculate the loglikelihood for every data point.

Value

The named list with parameters.

Examples

# avoid clusters of size < 60
Vb <- vb(1, dim=4, numst=2)
set.seed(12345)
hmmvb <- hmmvbTrain(iris[,1:4], VbStructure=Vb)
clust <- hmmvbClust(iris[,1:4], model=hmmvb, control=clustControl(minSize=60))
show(clust)

HDclust

Clustering High Dimensional Data with Hidden Markov Model on Variable Blocks

v1.0.3

GPL (>= 2)

Authors

Yevhen Tupikov [aut], Lin Lin [aut], Lixiang Zhang [aut], Jia Li [aut, cre]

Initial release

2019-04-05