modelTuner_loo

trainData

Output from <code><a rd-options="" href="/link/tune.instructions?package=OmicsMarkeR&version=1.4.2" data-mini-rdoc="OmicsMarkeR::tune.instructions">tune.instructions</a></code>.  Facilitates the
optimization by avoiding redundant model fitting.

guide

Vector of strins listing models to be fit

method

Indicies for cross-validated training models

inTrain

Indicies for cross-validated testing models

outTrain

Logical argument dictating if should save the
prediction data.  Default <code>savePredictions = FALSE</code>

savePredictions

Logical argument dictating if parallel processing is
allowed via foreach package

allowParallel

Character argument specifying how much output progress
to print.  Options are 'none', 'minimal' or 'full'.

verbose

List of additional arguments provided in the initial
classification and features selection function

theDots


Optimizes each model via LOO CV based upon the parameters
provided either by the internal <code><a rd-options="" href="/link/denovo.grid?package=OmicsMarkeR&version=1.4.2" data-mini-rdoc="OmicsMarkeR::denovo.grid">denovo.grid</a></code>
function or by the user.


Tools for classification and feature selection for 'omics' level
datasets.  It is a tool to provide multiple multivariate classification
and feature selection techniques complete with multiple stability metrics
and aggregation techniques.  It is primarily designed for analysis of
metabolomics datasets but potentially extendable to proteomics and
transcriptomics applications.

Charles Jr

OmicsMarkeR

Classification and Feature Selection for 'Omics' Datasets

modelTuner_loo function

Output from <code><a href="tune.instructions" rd-options="">tune.instructions</a></code>.  Facilitates the
optimization by avoiding redundant model fitting.

Optimizes each model via LOO CV based upon the parameters
provided either by the internal <code><a href="denovo.grid" rd-options="">denovo.grid</a></code>
function or by the user.

modelTuner_loo: Model Tuner for Leave-One-Out Cross-Validation

Description

Usage

Arguments

Value