train.RFs: Train and validate the operon classifier and evaluate the feature importance.
Description
Internal function to train an operon classifier to distinguish operon pairs (OPs) from non-operon pairs (NOPs)
on a given RNA-seq expression profile.
Usage
train.RFs(data, class, run = 30, p = 0.9, ntr = 1000, mtree = 4, verbose = TRUE, ...)
Arguments
data
Training/test data. See select.ops and select.nops.
class
Vector of the class labels.
run
Number of runs of training/validation. Default values is 30.
p
Percentage of samples to be used for the training. Default values is 0.9.
ntr
Number of trees to use in the operon classifier. Default values is 1000.
mtree
Number of variables randomly sampled as candidates at each split in each tree. Default values is 4.
verbose
Default logical value is TRUE.