Significance Level for Random Forest Impurity Importance Scores

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Documentation for package ‘RFlocalfdr’ version 0.8.5

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

count_variables	count the number of times each variable is used in a ranger random forest
determine.C	determine.C
determine_cutoff	evaluate a measure that can be used to determining a significance level for the Mean Decrease in Impurity measure returned by a Random Forest model
dsn	my.dsn
f.fit	fit a spline to the histogram of imp
fit.to.data.set	fit.to.data.set
fit.to.data.set.wrapper	fit.to.data.set.wrapper
imp20000	20000 importance values
local.fdr	local fdr
my.dsn	my.dsn
my.test1fun	my.test1fun
my_PIMP	my_PIMP based on the PIMP function from the vita package. ‘PIMP’ implements the test approach of Altmann et al. (2010) for the permutation variable importance measure ‘VarImp’ returned by the randomForest package (Liaw and Wiener (2002)) for classification and regression.
my_ranger_PIMP	my_ranger_PIMP based on the PIMP function from the vita package. ‘PIMP’ implements the test approach of Altmann et al. (2010) for the permutation variable importance measure ‘VarImp’ returned by the randomForest package (Liaw and Wiener (2002)) for classification and regression.
plotQ	plotQ
propTrueNullByLocalFDR	propTrueNullByLocalFDR
psn	my.dsn
qsn	my.dsn
run.it.importances	run.it.importances
significant.genes	significant.genes