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NodeTreePlot()
: plots the results of each node of a
conditional inference treePerfsRegression()
: performance measures for regression
tasksPerfsBinClassif()
: performance measures for binary
classification tasksNodesInfo()
: informations for each terminal node of a
conditional inference treeTreeStab()
: assesses the stability of a conditional
inference tree by using bootstrap replicationsNiceTreePlot()
: new arguments (cex and justmin)GetSplitStats()
: new summary element in the results +
the function is no longer compatible with trees from the
party
packagevip
packagevip
packageNiceTreePlot()
: plots conditional inference treesEasyTreeVarImp()
: variable importance for conditional
inference treesctreeUI()
and ctreeServer()
: shiny module
to build and analyse conditional inference treesictree()
: interactive (shiny) app for conditional
inference treesGetSplitStats()
: results have been rearranged and a
‘ratio’ column has been addedGetInteractionData()
: measures second order
interactions between the covariates of a random forestGetPartialData()
: computes partial dependencies of the
covariates of a random forestggForestEffects()
: plots the effects of the covariates
of a random forest in a ggplot dot plotggVarImp()
: plots variable importances of the
covariates of a random forest in a ggplot dot plotGetAleData()
: bug fix for regression tasksThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.