rtemis (version 0.79)

resLearn: rtemis internal: Resample Learn

Description

Train an rtemis learner on a set of resamples

Usage

resLearn(x, y, mod, resample.rtset = rtset.cv.resample(),
  weights = NULL, params = list(), verbose = TRUE,
  res.verbose = FALSE, trace = 0, save.mods = TRUE, outdir = NULL,
  n.cores = rtCores, parallel.type = ifelse(.Platform$OS.type ==
  "unix", "fork", "psock"))

Arguments

x

features - training set

y

outcome - training set

mod

String: rtemis model. See modSelect gives available models

resample.rtset

List: output of rtset (or a list of same structure)

params

List of named elements, each is a single value

verbose

Logical: If TRUE, print messages to screen

res.verbose

Logical: Will be passed to each mod's verbose argument

save.mods

Logical: If TRUE, save all models, otherwise discard after training. Use with elevate when training a large number of resamples. Default = TRUE

outdir

String: Path to save output. Default = NULL

Details

Input: features (x) and outcome (y) Procedure: resample, train learners Output: trained learners This is used internally by elevate and for bagging, when the bag.resampler argument is set in a learner.