tdmDefaultsFill: Default values for list 'tdm'.
In TDMR: Tuned Data Mining in R

Description Usage Arguments Details Value Note Author(s)

This list controls the tuning and unbiased evaluation phase. When called with tdm = tdmDefaultsFill(), a new list tdm is created and returned. When called with tdm = tdmDefaultsFill(mainFile="my.r", a new list tdm is created and returned, with the element mainFile set to the specified value. When called with tdm = tdmDefaultsFill(tdm), an existing list tdm is filled with further default values.

1	tdmDefaultsFill(tdm = NULL, mainFile = NULL)

`tdm`	(optional)
`mainFile`	(optional) if given, create or overwrite tdm$mainFile with this value

If tdm$mainFunc is missing, but tdm$mainFile exists, then tdmDefaultsFill will set

1	tdm$mainFunc=sub(".r","",basename(tdm$mainFile),fixed=TRUE)

tdm the new / extended list, where additional elements, if they are not yet def'd, are set as:

`mainFile`	[NULL] if not NULL, source this file from the current dir. It should contain the definition of tdm$mainFunc.
`mainFunc`	`sub(".r","",basename(tdm$mainFile),fixed=TRUE)`, if `tdm$mainFile` is set and `tdm$mainFunc` is NULL, else `"mainFunc"` This is the name of the function called in `tdmStartSpot2` and `unbiasedRun`
`unbiasedFunc`	["unbiasedRun"] which function to call for unbiased evaluation
`tuneMethod`	["spot"] other choices: "cmaes", "bfgs", ..., see `tdmDispatchTuner`
`nExperim`	[1]
`umode`	["RSUB"], one out of [ "RSUB" \| "CV" \| "TST" \| "SP_T" ], see `unbiasedRun`
`timeMode`	[1] 1: proc time, 2: system time, 3: elapsed time (columns `Time.TST` and `Time.TRN` in `envT$theFinals`
`filenameEnvT`	filename where `tdmBigLoop` will save a small version of environment `envT`. If NULL, it is set to `sub(".conf",".RData",tdm$runList[1])`.
`theSpotPath`	[NA] use SPOT's package version
`parallelCPUs`	[1] 1: sequential, >1: parallel execution with this many CPUs (package `parallel`)
`parallelFuncs`	[NULL] in case tdm$parallelCPUs>1: a string vector with functions which are clusterExport'ed in addition to `tdm$mainFunc`.
`path`	[NULL] from where to load and save `envT` resp. `filenameEnvT`. If it is NULL, `tdm$path` is set to the actual working directory at the time when tdmEnvTMakeNew is executed.
`runList`	[NULL] a list of configuration names `.conf`
`stratified`	[NULL] see `tdmReadAndSplit`
`tdmPath`	[NULL] from where to source the R sources. If NULL load library TDMR instead.
`test2.string`	["default cutoff"]
`optsVerbosity`	[0] the verbosity for the unbiased runs
`withParams`	[TRUE] list the columns with tuned parameter in final results
`nrun`	[5] number of runs for unbiased run
`U.saveModel`	[TRUE] if TRUE, save the last model, which is trained in unbiasedRun, onto `filenameEnvT`
`tstCol`	["TST.COL"] opts$TST.COL for unbiased runs (only for umode="TST")
`nfold`	[10] number of CV-folds for unbiased runs (only for umode="CV")
`TST.trnFrac`	[NULL] train set fraction (of all train-vali data),OVERWRITES opts$TST.trnFrac if not NULL.
`TST.valiFrac`	[NULL] validation set fraction (of all train-vali data), OVERWRITES to opts$TST.valiFrac if not NULL.
`TST.testFrac`	[0.2] test set fraction (of all data) for unbiased runs (only for umode="RSUB" or ="SP_T")
`CMA.propertyFile`	[NULL] (only for CMA-ES Java tuner) see `cma_jTuner`.
`CMA.populationSize`	[NULL] (only for CMA-ES Java tuner) see `cma_jTuner`.

The settings tdm$TST.trnFrac and tdm$TST.valiFrac allow to set programmatically certain values for opts$TST.trnFrac and opts$TST.valiFrac *after* opts has been constructed. So use tdm$TST.trnFrac and tdm$TST.valiFrac with CAUTION!

For tdm$timeMode, the 'user time' is the CPU time charged for the execution of user instructions of the calling process. The 'system time' is the CPU time charged for execution by the system on behalf of the calling process. The 'elapsed time' is the 'real' (wall-clock) time since the process was started.

Wolfgang Konen, THK, Patrick Koch

TDMR documentation built on March 3, 2020, 1:06 a.m.