modelTuner_loo: Model Tuner for Leave-One-Out Cross-Validation
In cdeterman/OmicsMarkeR: Classification and Feature Selection for 'Omics' Datasets

Description Usage Arguments Value Author(s)

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

1
2
3

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

`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