Version 2.17
mlr 2.17.0
CRAN release: 2020-01-10
plotting
-
n.show
argument had no effect inplotFilterValues()
. Thanks @albersonmiranda. (#2689)
Functional Data
-
Added several learners for regression and classification on functional data
- classif.classiFunc.(kernel|knn) (knn/kernel using various semi-metrics)
- (classif|regr).fgam (Functional generalized additive models)
- (classif|regr).FDboost (Boosted functional generalized additive models)
-
Added preprocessing steps for feature extraction from functional data
- extractFDAFourier (Fourier transform)
- extractFDAWavelets (Wavelet features)
- extractFDAFPCA (Principal components)
- extractFDATsfeatures (Time-Series features from tsfeatures package)
- extractFDADTWKernel (Dynamic Time-Warping Kernel)
- extractFDAMultiResFeatures (Compute features at multiple resolutions)
Fixed a bug where multiclass to binaryclass reduction techniques did not work with functional data.
Several other minor bug fixes and code improvements
Extended and clarified documentation for several fda components.
learners - general
- xgboost: added options ‘auto’, ‘approx’ and ‘gpu_hist’ to param
tree_method
(@albersonmiranda, #2701) -
getFeatureImportance()
now returns a long data.frame with columnsvariable
andimportance
. Beforehand, a wide data.frame was returned with each variable representing a column (@pat-s, #1755).
filters - general
- Allow a custom threholding function to be passed to filterFeatures and makeFilterWrapper (@annette987, #2686)
- Allow ensemble filters to include multiple base filters of the same type (@annette987, #2688)
filters - bugfixes
-
filterFeatures()
: Argthresh
was not working correctly when applied to ensemble filters. (@annette987, #2699) - Fixed incorrect ranking of ensemble filters. Thanks @annette987 (#2698)
mlr 2.17.1
CRAN release: 2020-03-24
Measures - bugixes
- remove measure
clValid::dunn
and its tests (package orphaned) (#2742) - Bugfix:
tuneThreshold()
now accounts for the direction of the measure. Beforehand, the performance measure was always minimized (#2732). - Remove adjusted Rsq measure (arsq), fixes #2711
Filters - bugfixes
- Fixed an issue which caused the random forest minimal depth filter to only return NA values when using thresholding. NAs should only be returned for features below the given threshold. (@annette987, #2710)
- Fixed problem which prevented passing filter options via argument
more.args
for simple filters (@annette987, #2709)
Feature selection - bugfixes
- Fix
print.FeatSelResult()
when bits.to.features is used inselectFeatures()
(#2721) - Return a long DF for
getFeatureImportance()
(#2708)
Misc
pkgdown: Move changelog to Appendix
Account for {checkmate} v2.0.0 update (#2734)
Refactor function calls from packages (
<pkg::fun>
) within ParamSets (#2730) to avoid errors inlistLearners()
if those pkgs are not installedlistLearners()
should not fail if a package is not installed (#2717)