o
New
3D graphics for tuning results and
their metamodels, using a twiddler-interface
on environment envT: see help(tdmPlotResMeta).
o
Print()
for TDMdata object “dataObj”
o
Fixed
the bug in tdmClassify (wrong ifelse
in applySVM).
o
Fixed
some minor bugs to reactivate parallel mode:
some sfExports were missing.
o
Fixed
the saveEnvT-bug (“[9:9]”) in tdmCompleteEval.
New option tdm$filenameEnvT.
o
Fixed
the tdmMapDesign bug (Design variables missing in
tdmMapDesign.csv and userMapDesign.csv would not be mapped to opts. Now missing variables are detected and an error is
thrown.)
o
Added
opts$SPLIT.SEED variable: a variable to decide if tdmSplitTestData runs deterministic
o
Added
opts$TST.trnFrac: now trnFrac
can be smaller than 1-opts$TST.valiFrac.
o
Added
SAVESEED-part in tdmSplitTestData, tdmClassifyLoop, tdmRegressLoop
o
Added
tdm$stratified with new meaning: if not NULL, make
stratified sampling w.r.t. the column of dset named
in tdm$stratified.
o
Some
minor fixes concerning data reading
o
TDM
docu now available in PDF and HTML format (TDM-docu.htm)
o integration of SFA (slow feature
analysis, see package rSFA on CRAN) as a
feature generation method for classification
o bug fix concerning tdmMapDesign;
extension of tdmMapDesign.csv
o moved PCA feature generation from
main_* into tdmClassifyLoop, it uses now only the
training data for establishing the PCA rotation (same for SFA)
o new training / validation / test set
capabilities, see Section “TDMR Data Reading
and Data Split …” in TDM-docu.pdf and tdmSplitTestData, tdmReadData.
o modified TDMR’s seed concept, new
option opts$*.seed = “algSeed” (get the seed from spotConfig$alg.seed)
o new parameter tdm$mainFunc,
simpler and more general usage (as compared to tdm$mainFile
and tdm$mainCommand)
o powell, cmaes, rSFA now in the “Depends” list of DESCRIPTION
o added a TDMR-package description (file tdmGeneralUtils.r)
o extended documentation (e.g. full docu for tdmOptsDefaultsSet
and many small other documentation extensions)
o new section opts$CLS.* for
classification-related settings
o bug fixes in demo01cpu (seed
variation) and demo02sonar (GD.DEVICE)
o merged former functions unbiasedBestRun_C and unbiasedBestRun_R
into only one function unbiasedRun
o extended functions for information on
class objects: print.TDMclassifier, print.tdmClass, print.TDMregressor,
print.tdmRegre
o removed the dependencies on packages
matlab and mlbench
o new function tdmParaBootstrap.r:
add parametric bootstrap patterns, if opts$ncopies>0
o new version of TDM-docu.pdf: see
documentation index – directory
o new demo: demo00sonar (with some
graphics)
o fix in print.TDMclassifier,
print.TDMregressor: optional argument ‘type’
o doc/index.html added
o doc/changes.html added (this file)
o initial version