Description Value Methods See Also Examples
This method generates and stores the final classifier corresponding
to an assessment. This classifier can then be used to classify new samples by
calling classifyNewSamples
. The final classifier is build according to the
classifier selected for a given assessment, applied on the whole data considering
only the genes selected by the feature selction method selected.
The methods returns an object of class assessment which finalClassifier has been build.
This method is only applicable on objects of class assessment.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | #dataPath <- file.path("C:", "Documents and Settings", "c.maumet", "My Documents", "Programmation", "Sources", "SVN", "R package", "data")
#aDataset <- new("dataset", dataId="vantVeer_70", dataPath=dataPath)
#aDataset <- loadData(aDataset)
data('vV70genesDataset')
# With the RFE-SVM as feature selection method
expeOfInterest <- new("assessment", dataset=vV70genes,
noFolds1stLayer=10,
noFolds2ndLayer=9,
classifierName="svm",
typeFoldCreation="original",
svmKernel="linear",
noOfRepeat=2,
featureSelectionOptions=new("geneSubsets", optionValues=c(1,2,4,8,16,32,64,70)))
# Build the final classifier
expeOfInterest <- findFinalClassifier(expeOfInterest)
# With the NSC as feature selection method
expeOfInterest <- new("assessment", dataset=vV70genes,
noFolds1stLayer=10,
noFolds2ndLayer=9,
featureSelectionMethod="nsc",
classifierName="nsc",
typeFoldCreation="original",
svmKernel="linear",
noOfRepeat=2,
featureSelectionOptions=new("thresholds"))
# Build the final classifier
expeOfInterest <- findFinalClassifier(expeOfInterest)
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