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MDFS (version 1.5.5)

MultiDimensional Feature Selection

Description

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. R. Piliszek et al. (2019) .

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Version

Install

install.packages('MDFS')

Monthly Downloads

359

Version

1.5.5

License

GPL-3

Maintainer

Radosław Piliszek

Last Published

December 12th, 2024

Functions in MDFS (1.5.5)

AddContrastVariables

Add contrast variables to data

ComputeInterestingTuples

Interesting tuples

ComputeMaxInfoGainsDiscrete

Max information gains (discrete)

Compute p-values from information gains and return MDFS

Get the recommended range for multiple discretisations

Discretize variable on demand

Run end-to-end MDFS

RelevantVariables.MDFS

Find indices of relevant variables from MDFS

ComputeInterestingTuplesDiscrete

Interesting tuples (discrete)

RelevantVariables

Find indices of relevant variables

ComputeMaxInfoGains

Max information gains

GenContrastVariables

Generate contrast variables from data

as.data.frame.MDFS

as.data.frame S3 method implementation for MDFS

An artificial dataset called MADELON

mdfs_omp_set_num_threads

Call omp_set_num_threads

Plot MDFS details