rfClass: Classify using Random Forests
In a4Classif: Automated Affymetrix Array Analysis Classification Package

Description Usage Arguments Value Note Author(s) References See Also Examples

View source: R/randomForest.R

Classify using the Random Forest algorithm of Breiman (2001)

1	rfClass(object, groups, probe2gene = TRUE)

`object`	object containing the expression measurements; currently the only method supported is one for ExpressionSet objects
`groups`	character string indicating the column containing the class membership
`probe2gene`	logical; if `TRUE` Affymetrix probeset IDs are translated into gene symbols in the output object; if `FALSE` no such translation is conducted

Object of class 'rfClass'

topTable and plot methods are available for 'rfClass' objects.

Tobias Verbeke and Willem Talloen

Breiman, L. (2001), Random Forests, Machine Learning 45(1), 5-32.

randomForest

if(require(ALL)){
 data(ALL, package = "ALL")
 ALL <- addGeneInfo(ALL)
 ALL$BTtype <- as.factor(substr(ALL$BT,0,1))
 # select only a subset of the data for computation time reason
 ALLSubset <- ALL[sample.int(n = nrow(ALL), size = 100, replace = TRUE), ]
 resultRf <- rfClass(object = ALLSubset, groups = "BTtype")
 plot(resultRf)
 topTable(resultRf, n = 15)
}