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 |
|
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"
numeric
Slot 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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