baseline: doOptim – R documentation

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doOptim

Optimise several baseline algorithms on a data set

Description

Tests several baseline algorithms with one predictor for a given data set. The baseline algorithms are represented as a list of baselineAlgTest objects, and the predictor as a predictionTest object.

Usage

doOptim(baselineTests, X, y, predictionTest, postproc = NULL,
        tmpfile = "tmp.baseline", verbose = FALSE, cleanTmp = FALSE)

Arguments

`baselineTests`	a list of `baselineAlgTest` objects. The baseline algorithms and parameter values to test
`X`	A matrix. The spectra to use in the test
`y`	A vector or matrix. The response(s) to use in the test
`predictionTest`	A `predictionTest` object. The predictor and parameter values to use in the test
`postproc`	A function, used to postprocess the baseline corrected spectra prior to prediction testing. The function should take a matrix of spectra as its only argument, and return a matrix of postprocessed spectra
`tmpfile`	The basename of the files used to store intermediate calculations for checkpointing. Defaults to `"tmp.baseline"`
`verbose`	Logical, specifying whether the test should print out progress information. Default is `FALSE`
`cleanTmp`	Logical, specifying whether the intermediate files should be deleted when the optimisation has finished. Default is `FALSE`

Details

The function loops through the baseline algorithm tests in baselineTests, testing each of them with the given data and prediction test, and collects the results. The results of each baseline algorithm test is saved in a temporary file so that if the optimisation is interrupted, it can be re-run and will use the pre-calculated results. If cleanTmp is TRUE, the temporary files are deleted when the whole optimisation has finished.

Value

A list with components

`baselineTests`	The `baselineTests` argument
`results`	A list with the `baselineAlgResult` objects for each baseline test
`minQualMeas`	The minimum quality measure value
`baselineAlg.min`	The name of the baseline algorithm giving the minimum quality measure value
`param.min`	A list with the parameter values corresponding to the minimum quality measure value

Author(s)

Bjørn-Helge Mevik and Kristian Hovde Liland