plotFilterValues: Plot filter values using ggplot2.

In riebetob/mlr: Machine Learning in R

Description

Plot filter values using ggplot2.

Usage

plotFilterValues(fvalues, sort = "dec", n.show = 20L,
  feat.type.cols = FALSE, facet.wrap.nrow = NULL, facet.wrap.ncol = NULL)

Arguments

fvalues	[FilterValues] Filter values.
sort	[character(1)] Sort features like this. “dec” = decreasing, “inc” = increasing, “none” = no sorting. Default is decreasing.
n.show	[integer(1)] Number of features (maximal) to show. Default is 20.
feat.type.cols	[logical(1)] Colors for factor and numeric features. FALSE means no colors. Default is FALSE.
facet.wrap.nrow, facet.wrap.ncol	[integer()] Number of rows and columns for facetting. Default for both is NULL. In this case ggplot's facet_wrap will choose the layout itself.

Value

ggplot2 plot object.

See Also

Other filter: filterFeatures, generateFilterValuesData, getFilterValues, getFilteredFeatures, listFilterMethods, makeFilterWrapper, makeFilter, plotFilterValuesGGVIS

Other generate_plot_data: generateCalibrationData, generateCritDifferencesData, generateFeatureImportanceData, generateFilterValuesData, generateFunctionalANOVAData, generateLearningCurveData, generatePartialDependenceData, generateThreshVsPerfData, getFilterValues

Examples

fv = generateFilterValuesData(iris.task, method = "variance")
plotFilterValues(fv)

riebetob/mlr documentation built on May 20, 2019, 5:58 p.m.