kMeansThresholding: Thresholds by k-Means clustering

Description Usage Arguments Value Note

Description

This function calculates thresholds by using k-Means clustering. The number of clusters is automatically derived by the Schwarz Bayesian criterion

Usage

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kMeansThresholding(df, n.clust = NULL, G = 25, size.data = NULL,
  size.sample = 5000, seed = 123, iter.max = 5000)

Arguments

df

input data frame

n.clust

number of initial cluster (Default: NULL)

G

see Mclust. Default: 25

size.data

percentage of input data used in anaylsis. Default: NULL

size.sample

sample in initialization of Mclust in order to speed up the process. Default: 5000, to use full data set to NULL

seed

set seed. Default: 123

iter.max

number of iterlations in Mclust. Default: 5000

Value

vector containing the cluster centers

Note


ggRaver/Lslide documentation built on June 20, 2019, 2:29 p.m.