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Plot filter values using ggplot2.
plotFilterValues( fvalues, sort = "dec", n.show = nrow(fvalues$data), filter = NULL, feat.type.cols = FALSE )
(FilterValues) Filter values.
(character(1)) Available options are:
character(1)
"dec"-> descending
"dec"
"inc" -> increasing
"inc"
"none" -> no sorting
"none"
Default is decreasing.
(integer(1)) Number of features (maximal) to show. Default is to plot all features.
integer(1)
(character(1)) In case fvalues contains multiple filter methods, which method should be plotted?
fvalues
(logical(1)) Whether to color different feature types (e.g. numeric | factor). Default is to use no colors (feat.type.cols = FALSE).
logical(1)
feat.type.cols = FALSE
ggplot2 plot object.
Other filter: filterFeatures(), generateFilterValuesData(), getFilteredFeatures(), listFilterEnsembleMethods(), listFilterMethods(), makeFilterEnsemble(), makeFilterWrapper(), makeFilter()
filterFeatures()
generateFilterValuesData()
getFilteredFeatures()
listFilterEnsembleMethods()
listFilterMethods()
makeFilterEnsemble()
makeFilterWrapper()
makeFilter()
Other generate_plot_data: generateCalibrationData(), generateCritDifferencesData(), generateFeatureImportanceData(), generateFilterValuesData(), generateLearningCurveData(), generatePartialDependenceData(), generateThreshVsPerfData()
generateCalibrationData()
generateCritDifferencesData()
generateFeatureImportanceData()
generateLearningCurveData()
generatePartialDependenceData()
generateThreshVsPerfData()
# NOT RUN { fv = generateFilterValuesData(iris.task, method = "variance") plotFilterValues(fv) # }
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