Description Arguments Value Methods Author(s) See Also Examples
This method provides an easy interface to modify the attributes of the object of class
featureSelectionOptions related to a particular assessment, directly from this object assessment.
The argument topic specifies which part of the featureSelectionOptions is of interest.
This method is only available none of the one-layer
CV or two-layers CV have been performed and the final classifier has not been determined yet.
object |
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topic |
if the |
The methods modifies the object of class assessment and returned the slot modified
accordingly to the request provided by topic.
If topic is missing
object of class featureSelectionOptions featureSelectionOptions corresponding to the assessment is replaced by value.
If topic is "optionValues"
numeric Slot optionValues of the featureSelectionOptions is replaced by value.
If topic is "noOfOptions"
numeric Slot noOfOptions of the featureSelectionOptions is replaced by value.
If object is of class geneSubsets and topic is "maxSubsetSize"
numeric Slot maxSubsetSize of the geneSubsets is replaced by value.
If object is of class geneSubsets and topic is "subsetsSizes"
numeric Slot optionValues of the geneSubsets is replaced by value.
If object is of class geneSubsets and topic is "noModels"
numericSlot noOfOptions of the geneSubsets is replaced by value.
If object is of class geneSubsets and topic is "speed"
numeric Slot speed of the geneSubsets is replaced by value.
If object is of class thresholds and topic is "thresholds"
numeric Slot optionValues of the object of class thresholds is replaced by value.
If object is of class thresholds and topic is "noThresholds"
numeric Slot noOfOptions of the object of class thresholds is replaced by value.
The method is only applicable on objects of class assessment.
Camille Maumet
featureSelectionOptions, 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 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | # With an assessment using RFE
data('vV70genesDataset')
mySubsets <- new("geneSubsets", optionValues=c(1,2,3,4,5,6))
myExpe <- new("assessment", dataset=vV70genes,
noFolds1stLayer=10,
noFolds2ndLayer=9,
classifierName="svm",
typeFoldCreation="original",
svmKernel="linear",
noOfRepeat=2,
featureSelectionOptions=mySubsets)
# Modify the size of the biggest subset
getFeatureSelectionOptions(myExpe, topic='maxSubsetSize') <- 70
getFeatureSelectionOptions(myExpe, topic='maxSubsetSize')
# Modify all the sizes of subsets
getFeatureSelectionOptions(myExpe, topic='subsetsSizes') <- c(1,5,10,25,30)
getFeatureSelectionOptions(myExpe, topic='subsetsSizes')
# Modify the speed
getFeatureSelectionOptions(myExpe, topic='speed') <- 'slow'
getFeatureSelectionOptions(myExpe, topic='speed')
# Modify the entire geneSubsets
getFeatureSelectionOptions(myExpe) <- mySubsets
getFeatureSelectionOptions(myExpe, topic='maxSubsetSize')
getFeatureSelectionOptions(myExpe, topic='subsetsSizes')
getFeatureSelectionOptions(myExpe, topic='speed')
getFeatureSelectionOptions(myExpe, topic='noModels')
# With an assessment using NSC as a feature selection method
myThresholds <- new("thresholds", optionValues=c(0.1,0.2,0.3))
myExpe2 <- new("assessment", dataset=vV70genes,
noFolds1stLayer=10,
noFolds2ndLayer=9,
classifierName="nsc",
featureSelectionMethod='nsc',
typeFoldCreation="original",
svmKernel="linear",
noOfRepeat=2,
featureSelectionOptions=myThresholds)
otherThresholds <- new("thresholds", optionValues=c(0,0.5,1,1.5,2,2.5,3))
# Modify the whole object 'featureSelectionOptions' (an object of class thresholds)
getFeatureSelectionOptions(myExpe2) <- otherThresholds
getFeatureSelectionOptions(myExpe2, topic='thresholds')
getFeatureSelectionOptions(myExpe2, topic='noThresholds')
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