determineClusterNumber: Determine the best cluster numbers

In ProfessionalFarmer/loonR: Common function in bioinformatics analysis

Determine the best cluster numbers

Description

Determine the best cluster numbers

Usage

determineClusterNumber(
  df,
  distance = "euclidean",
  method = "kmeans",
  dissimilarity = NULL,
  min.nc = 2,
  max.nc = 8
)

Arguments

df	Row is sample and column is variable
distance	This must be one of: "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski" or "NULL".
method	kmeans. the cluster analysis method to be used. This should be one of: "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", "centroid", "kmeans".
dissimilarity	dissimilarity matrix to be used. By default, diss=NULL, but if it is replaced by a dissimilarity matrix, distance should be "NULL".
min.nc	2 minimal number of clusters
max.nc	8 maximal number of clusters, between 2 and (number of objects - 1), greater or equal to min.nc.

ProfessionalFarmer/loonR documentation built on Oct. 9, 2024, 9:56 p.m.