runOneLayerExtCV-methods {magpie}R Documentation

runOneLayerExtCV: Method to run an external one-layer cross-validation

Description

This method run an external one-layer cross-validation according to the options stored in an object of class experiment. The concept of external cross-validation has been introduced by G.J. McLachlan and C. Ambroise in 'Selection bias in gene extraction on the basis of microarray gene-expression data' (cf. section References). This technique of cross-validation is used to determine an unbiased estimate of the error rate when feature selection is involved.

Arguments

object Object of class experiment. Object experiment of interest

Value

object of class experiment in which the one-layer external cross-validation has been computed, therfore, the slot resultRepeated1LayerCV is no more NULL. This methods print out the key results of the experiment, to access the full detail of the results, the user must call the method getResults.

Methods

object = "experiment"
This method is only applicable on objects of class experiment.

References

C. Amboise and G.J. McLachlan 2002. selection bias in gene extraction on the basis of microarray gene-expression data. PNAS, 99(10):6562-6566

See Also

experiment, getResults, runTwoLayerExtCV-methods

Examples

data('vV70genesDataset')

# Experiment with RFE and SVM
myExpe <- new("experiment", dataset=vV70genes,
                   noFolds1stLayer=9,
                   noFolds2ndLayer=10,
                   classifierName="svm",
                   typeFoldCreation="original",
                   svmKernel="linear",
                   noOfRepeat=2,
                   featureSelectionOptions=new("geneSubsets", optionValues=c(1,2,3,4,5,6)))

myExpe <- runOneLayerExtCV(myExpe)

[Package magpie version 0.2.0 Index]