Knowledge-Based Guided Regularized Random Forest

Documentation for package ‘KnowGRRF’ version 1.0

get.performance	Get performance of feature selection
on.aic	AIC from model built with KnowGRRF, functions used in optimization to find scaling parameter for rrf.opt.1 or rrf.opt.m
rf.once	Build random forest once and return AUC for both training and test set if available
rf.repeat	Build random forest multiple times and return AUC for both training and test set if available
rrf.once	Feature selection by regularized random forest and compare against full model
rrf.opt.1	KnowGRRF with weights from one knowledge domain
rrf.opt.m	KnowGRRF with weights from multiple knowledge domain
select.stable	Select a set of stable features based on frequency picked by GRRF.
select.stable.aic	Select a set of stable features based on AIC after an initial selection by GRRF
write.roc	write test ROC to a data table.