runOneLayerExtCV-methods {Rmagpie} | R Documentation |
This method run an external one-layer cross-validation according to the options stored in an object of class assessment. 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.
object |
Object of class assessment . Object assessment of interest |
object of class assessment
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 assessment, to access the full detail
of the results, the user must call the method getResults
.
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
assessment
, getResults
, runTwoLayerExtCV-methods
data('vV70genesDataset') # assessment with RFE and SVM myExpe <- new("assessment", 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)