mlr 2.17.0 Unreleased

plotting

Functional Data

PR: #2638 (@pfistl)

  • 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)

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