clustering: Perform cluster analysis
In specmine: Metabolomics and Spectral Data Analysis and Mining

Description Usage Arguments Value Examples

Perform cluster analysis on the dataset.

1 2	clustering(dataset, method = "hc", distance = "euclidean", type = "samples", num.clusters = 5, clustMethod = "complete")

`dataset`	list representing the dataset from a metabolomics experiment.
`method`	a string describing the method of clustering. Possible types are: "hc" perform hierarchical clustering. "kmeans" perform kmeans clustering.
`distance`	the distance measure to be used to compute the distances between the rows of a data matrix. Possible types are "euclidean", "manhattan", "pearson" or "spearman". Only for hierarchical clustering.
`type`	a string indicating if cluster analysis will be performed on samples ("samples") or on variables ("variables").
`num.clusters`	the number of clusters in k-means cluster analysis.
`clustMethod`	Cluster method for hierarchical clustering.

An object of class kmeans or hclust with the clustering results.

  ## Example of kmeans and hierarchical clustering
  library(specmine.datasets)
  data(cachexia)
  hc.result = clustering(cachexia, method = "hc", 
	      distance = "euclidean")
  kmeans.result = clustering(cachexia, method = "kmeans", 
		  num.clusters = 4)