Rmagpie (version 1.28.0)

getFinalClassifier-methods: getFinalClassifier Method to access the attributes of a finalClassifier from an assessment

Description

This method provides an easy interface to access the attributes of the object of class finalClassifier related to a particular assessment, directly from this object assessment. The argument topic specifies which part of the finalClassifier is of interest.

Arguments

object

Object of class assessment. Object assessment of interest

topic

character. Optional argument that specifies which attribute of the finalClassifier is requested, the possible values are genesFromBestToWorst (slot genesFromBestToWorst of the finalClassifier), models (slot models of the finalClassifier), if the topic is missing then the whole finalClassifier object is returned.

Value

The value returned by the method changes accordingly to the topic argument.If topic is missing object of class finalClassifier the finalClassifier corresponding to the assessment of interestIf topic is "genesFromBestToWorst" numeric corresponding to the genesFromBestToWorst of the finalClassifierIf topic is "models" numeric corresponding to the models of the finalClassifier

Methods

object = "assessment"

The method is only applicable on objects of class assessment.

See Also

finalClassifier, assessment

Examples

#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)

mySubsets <- new("geneSubsets", optionValues=c(1,2,3,4,5,6))
data('vV70genesDataset')

# assessment with RFE and SVM
expeOfInterest <- new("assessment", dataset=vV70genes,
                               noFolds1stLayer=10,
                               noFolds2ndLayer=9,
                               classifierName="svm",
                               typeFoldCreation="original",
                               svmKernel="linear",
                               noOfRepeat=2,
                               featureSelectionOptions=mySubsets)

expeOfInterest <- findFinalClassifier(expeOfInterest)

# Return the whole object of class finalClassifier
getFinalClassifier(expeOfInterest)
getFinalClassifier(expeOfInterest, 'genesFromBestToWorst')
getFinalClassifier(expeOfInterest, 'models')

# assessment with NSC
expeOfInterest <- new("assessment", dataset=vV70genes,
                               noFolds1stLayer=10,
                               noFolds2ndLayer=9,
                               featureSelectionMethod='nsc',
                               classifierName="nsc",
                               typeFoldCreation="original",
                               svmKernel="linear",
                               noOfRepeat=2,
                               featureSelectionOptions=new("thresholds"))

expeOfInterest <- findFinalClassifier(expeOfInterest)

# Return the whole object of class finalClassifier
getFinalClassifier(expeOfInterest)
getFinalClassifier(expeOfInterest, 'genesFromBestToWorst')
getFinalClassifier(expeOfInterest, 'models')