MultiDimensional Feature Selection

Functions for MultiDimensional Feature Selection (MDFS): calculating multidimensional information gains, scoring variables, finding important variables, plotting selection results. This package includes an optional CUDA implementation that speeds up information gain calculation using NVIDIA GPGPUs.


1.0.3 | 2018-11-07

  • add note about recommended FDR control method

  • fix a possible memory error introduced in 1.0.2 (mismatched new/delete[] operators)

1.0.2 | 2018-10-31

  • improve default range estimation

  • allow overriding pseudo.count in MDFS function

  • set default p.adjust.method to default p.adjust method ("holm")

  • set default level to suggested FWER level (0.05)

  • fix CUDA version to not abruptly exit R on error

  • fix use.CUDA=T in MDFS function

1.0.1 | 2018-06-26

  • fix factors as input decision in ComputeMaxInfoGains, ComputeInterestingTuples and MDFS

  • fix adjusted.p.value in MDFS

  • return statistic and p.value in MDFS

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.0.5 by Radosław Piliszek, a year ago

Browse source code at

Authors: Radosław Piliszek [aut, cre] , Krzysztof Mnich [aut] , Paweł Tabaszewski [aut] , Szymon Migacz [aut] , Andrzej Sułecki [aut] , Witold Remigiusz Rudnicki [aut]

Documentation:   PDF Manual  

GPL-3 license

System requirements: C++11

See at CRAN