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.
doOptim(baselineTests, X, y, predictionTest, postproc = NULL,
tmpfile = "tmp.baseline", verbose = FALSE, cleanTmp = FALSE)A list with components
The baselineTests argument
A list with the baselineAlgResult objects
for each baseline test
The minimum quality measure value
The name of the baseline algorithm giving the minimum quality measure value
A list with the parameter values corresponding to the minimum quality measure value
a list of baselineAlgTest
objects. The baseline algorithms and parameter values to test
A matrix. The spectra to use in the test
A vector or matrix. The response(s) to use in the test
A predictionTest object. The
predictor and parameter values to use in the test
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
The basename of the files used to store intermediate
calculations for checkpointing. Defaults to "tmp.baseline"
Logical, specifying whether the test should print out
progress information. Default is FALSE
Logical, specifying whether the intermediate files should
be deleted when the optimisation has finished. Default is FALSE
Bjørn-Helge Mevik and Kristian Hovde Liland
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.
baselineAlgTest,predictionTest