MLIclust {MLInterfaces}R Documentation

An interface to various unsupervised machine learning methods for ExpressionSets

Description

This document describes a family of wrappers to R functions that perform clustering of multivariate datasets. For example, the kmeansB function is a wrapper for a call to kmeans for objects of class ExpressionSet. The interfaces of MLInterfaces provide a common calling sequence and common return value for machine learning code.

Usage

kmeansB(exprObj, k , iter.max, metric = "euclidean") 

Arguments

exprObj An instance of the exprset class.
k The number of clusters
iter.max The maximum number of iterations to perform.
metric See knn for a complete description.

Details

See kmeans for a complete description, and for other functions named [f]B, see the documentation on f.

Value

An object of class clustOutput-class.

Author(s)

Jess Mar, VJ Carey <stvjc@channing.harvard.edu>

See Also

ldaB

Examples

##get these from the source files
library(golubEsets)
data(Golub_Merge)
smallG <- Golub_Merge[1:60,]
set.seed(1234) # needed for nnet initialization
kmeansB( smallG, k=4 )
agnesB( smallG, k=5, height=0, FALSE )
dianaB( smallG, k=5, height=0, FALSE )
pamB( smallG, k=5, height=0, FALSE )
bclustB( smallG, k=5, height=0 )
cmeansB( smallG, k=5, height=0 )
cshellB( smallG, k=5, height=0 , iter.max=1)
#lcaB( BsmG, k=3 )
hclustB( smallG, k=4 )
hclustB( smallG, height=40000 )

[Package MLInterfaces version 1.10.3 Index]