CRAN/E | flevr

flevr

Flexible, Ensemble-Based Variable Selection with Potentially Missing Data

Installation

About

Perform variable selection in settings with possibly missing data based on extrinsic (algorithm-specific) and intrinsic (population-level) variable importance. Uses a Super Learner ensemble to estimate the underlying prediction functions that give rise to estimates of variable importance. For more information about the methods, please see Williamson and Huang (2023+) .

github.com/bdwilliamson/flevr
Bug report File report

Key Metrics

Version 0.0.4
R ≥ 3.1.0
Published 2023-11-30 151 days ago
Needs compilation? no
License MIT
License File
CRAN checks flevr results

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Maintainer

Maintainer

Brian D. Williamson

brian.d.williamson@kp.org

Authors

Brian D. Williamson

aut / cre

Material

README
NEWS
Reference manual
Package source

Vignettes

Extrinsic variable selection
Intrinsic variable selection
Introduction to 'flevr'

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 3.1.0

Imports

SuperLearner
dplyr
magrittr
tibble
caret
mvtnorm
kernlab
rlang
ranger

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