modelTuner: Model Tuner

In cdeterman/OmicsMarkeR: Classification and Feature Selection for 'Omics' Datasets

Description

Optimizes each model based upon the parameters provided either by the internal denovo.grid function or by the user.

Usage

modelTuner(trainData, guide, method, inTrain, outTrain, lev,
  savePredictions = FALSE, allowParallel = FALSE, verbose = "none",
  theDots = NULL)

Arguments

trainData	Data used to fit the model
guide	Output from tune.instructions. Facilitates the optimization by avoiding redundant model fitting.
method	Vector of strins listing models to be fit
inTrain	Indicies for cross-validated training models
outTrain	Indicies for cross-validated testing models
lev	Group levels
savePredictions	Logical argument dictating if should save the prediction data. Default savePredictions = FALSE
allowParallel	Logical argument dictating if parallel processing is allowed via foreach package
verbose	Character argument specifying how much output progress to print. Options are 'none', 'minimal' or 'full'.
theDots	List of additional arguments provided in the initial classification and features selection function

Value

Returns list of fitted models

Author(s)

Charles E. Determan Jr.

cdeterman/OmicsMarkeR documentation built on May 13, 2019, 2:35 p.m.