pvimPlot: Gini importance and permutation-based variable importance...

In statTarget: Statistical Analysis of Molecular Profiles

Description

Create plots for Gini importance and permutation-based variable Gini importance measures.

Usage

pvimPlot(rForest,pimpModel,nvarRF = 6,border= NA,
space = 0.3,...)

Arguments

rForest	an object of class randomForest that contains the proximity component from statTarget rForest function.
pimpModel	an object of permutation-based variable Gini importance measures (PIMP-algorithm) from statTarget rForest function.
nvarRF	The number of variables in importance plot of randomForest.
border	The color to be used for the border of the bars. Use border = NA to omit borders. see also barplot.
space	The amount of space (as a fraction of the average bar width) left before each bar. May be given as a single number or one number per bar. see also barplot
...	A generic barplot function from graphics package.

Value

The output of the name of selected variable importance.

Author(s)

Hemi Luan, [e-mail]

Examples

datpath <- system.file('extdata',package = 'statTarget')
statFile <- paste(datpath,'data_example.csv', sep='/')
getFile <- read.csv(statFile,header=TRUE)
rFtest <- rForest(getFile,ntree = 10,times = 5)
pvimPlot(rFtest$randomForest,rFtest$pimpTest)

statTarget documentation built on Nov. 8, 2020, 8:27 p.m.