kMeansThresholding: Thresholds by k-Means clustering

In ggRaver/Lslide: Functions for object-oriented image analysis in landslide science

Thresholds by k-Means clustering

Description

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

Usage

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

• see mclust (last call: 13-04-2017)

• see kmeans (last call: 13-04-2017)

ggRaver/Lslide documentation built on April 8, 2022, 7:14 a.m.