number_of_clusters: Title LASSO

In HBPMedical/CCC: A wrapper to run the 3C methodology

Description

Title LASSO

Usage

number_of_clusters(x, method = "Euclidean", K.max = 10, B = 100,
  verbose = FALSE, plot.num.clus = TRUE, scale = TRUE, diss = FALSE,
  cluster.only = TRUE)

Arguments

x	Data matrix
method	character string indicating how the “optimal” number of clusters: Euclidean (default), Manhattan, heirarchical euclidean or heirarchcal manhattan
K.max	the maximum number of clusters to consider, must be at least two. Default value is 10.
B	integer, number of Monte Carlo (“bootstrap”) samples. Default value is 100.
verbose	integer or logical, determining if “progress” output should be printed. The default prints one bit per bootstrap sample. Default value is FALSE.
plot.num.clus	if TRUE (default) the gap statistic plot will be printed
scale	if TRUE (default) the data matrix will be scaled.
diss	if TRUE (default as FALSE) x will be considered as a dissimilarity matrix.
cluster.only	if true (default as FALSE) only the clustering will be computed and returned, see details.
y	Dependent variable
x	Data matrix

Value

plot and table which advises how many clusters should be

plot and table which advises how many clusters should be

Examples

# LASSO_selection(x, y)
Title Deciding on Number of Clusters

# number_of_clusters(subx, B=50, method='Euclidean')

HBPMedical/CCC documentation built on May 28, 2019, 12:40 p.m.