train.RFs: Train and validate the operon classifier and evaluate the...

In CONDOP: Condition-Dependent Operon Predictions

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.

Author(s)

Vittorio Fortino

CONDOP documentation built on May 2, 2019, 1:26 p.m.