R Observatory: Metrics for mlr3fselect version 1.7.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

mlr3fselect

1.7.0Package record

Feature Selection for 'mlr3'

2packages dependsuggested by 1

62.5Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Marc BeckerCRAN page ↗GitHub ↗Website ↗Issues ↗

Feature selection package of the 'mlr3' ecosystem. It selects the optimal feature set for any 'mlr3' learner. The package works with several optimization algorithms e.g. Random Search, Recursive Feature Elimination, and Genetic Search. Moreover, it can automatically optimize learners and estimate the performance of optimized feature sets with nested resampling.

Changes in 1.7.0

fix: Errors raised by mlr3fselect are structured conditions with the Mlr3Error class now, so they can be caught by class and are formatted with cli (#198).
fix: Loading the package repeatedly duplicated the entries that mlr3fselect adds to the reflections of bbotk and mlr3 (#199).
fix: ArchiveAsyncFSelect pushed results with the removed rush::Rush$push_results() method.
fix: EnsembleFSResult$pareto_front() correctly now handles ties in the pareto front: in edge cases, it returned dominated points for minimizing measures and discarded the true front for maximizing measures (#170).
fix: ensemble_fselect() dropped the importance column for subclasses of FSelectorBatchRFE. The column is now added whenever the feature selection result contains importance scores (#195).
fix: embedded_ensemble_fselect() instantiated the [mlr3::Resampling] passed to init_resampling by reference, so the resampling of the user was changed and reused the row ids of the first task when applied to another task (#179).
fix: EnsembleFSResult$knee_points() silently returned a row of NA when the Pareto front did not span a range in both dimensions. The first point of the Pareto front is returned with a warning now (#171).
fix: EnsembleFSResult$stability() cached the results by stability measure only, so the same measure requested with different stability_args returned the cached value of the first call (#189).
fix: ensemble_fselect() and embedded_ensemble_fselect() failed with a cryptic error when a single [mlr3::Learner] was passed to the learners argument because the result of as_learners() was discarded (#178).
fix: extract_inner_fselect_archives() ignored the exclude_columns argument because it was passed positionally to as.data.table() where it landed in the ... argument (#180).
fix: as.data.table() on an ArchiveBatchFSelect returned the n_features column as a list column instead of an integer column, so operations such as sort() failed with 'x' must be atomic (#181).
fix: fs("sequential")$optimization_path() returned the first evaluated feature set of each batch instead of the best one, so the selected feature set was usually missing from the reported path (#182).

Show all changes in 1.7.0Hide the rest of the changes in 1.7.0

fix: fs("rfecv") left the resampling of the objective set to an insample resampling, so subsequent evaluations on the same instance silently resampled in-sample (#187).
fix: The mlr3fselect.backup callback deleted the backup of the previous batch before it wrote the new one, so a crash in between lost the complete run. The benchmark result is now written to a temporary file and renamed afterwards (#188).
BREAKING CHANGE: The mlr3fselect.backup callback requires the path argument now. Previously it wrote a bmr.rds file into the working directory of the user (#188).
fix: as.data.table() on an EnsembleFSResult accepts the documented benchmark_result argument now to omit the task, learner and resampling columns (#190).
fix: The $print() methods of ArchiveBatchFSelect, ArchiveAsyncFSelect, ArchiveAsyncFSelectFrozen, AutoFSelector and FSelector errored with unused argument when arguments such as digits were passed (#190).
fix: fs("rfecv") had the same label as fs("rfe"), so both were indistinguishable in as.data.table(mlr_fselectors). Its manual page also instructed to construct it with fs("rfe") (#191).
fix: AutoFSelector ignored the predict_type when the final model was fitted, so $predict() returned response predictions although e.g. "prob" was set. Errors raised while setting the predict type on the final model are not swallowed anymore (#184).
fix: The $archive, $learner, $fselect_instance and $fselect_result bindings of AutoFSelector are read-only now. Previously an assignment failed with unused argument instead of the usual read-only error (#186).
fix: AutoFSelector$train() did not check the row ids of an instantiated inner resampling for cross-validation and reported a wrong set number for holdout (#197).
fix: fs("shadow_variable_search") left the shadow variables in the task, domain and search space of the instance when the feature selection was aborted because the first selected feature was a shadow variable (#183).
fix: ArchiveBatchFSelect$best() and ArchiveAsyncFSelect$best() returned an empty table or a row of missing values when a single score in the archive was NA. Missing scores are now skipped. ArchiveAsyncFSelect$best() also ignored the ties_method set during construction (#177).
fix: The mlr3fselect.svm_rfe callback accepted support vector machines without a type or kernel setting, although only type = "C-classification" and kernel = "linear" are supported. The callback now also errors on multi-class tasks for which the importance scores are not defined (#173).
fix: The asynchronous feature selection ignored the always_included column role. Columns with this role were excluded from the models instead of being added to every feature subset (#175).
fix: The mlr3fselect.one_se_rule callback errored on archives with a single evaluation or with missing scores, and wrote the n_features column as a list column instead of an integer column (#174).
fix: extract_inner_fselect_results() added the iteration and fselect_instance columns to the result of the inner FSelectInstance by reference, which created a circular reference between the instance and its own result (#172).
fix: fs("rfe") and fs("rfecv") failed with an internal data.table error when store_benchmark_result = FALSE was set because the importance scores were read from the benchmark result of the archive (#169).
fix: fs("rfecv", recursive = FALSE) failed with an internal data.table error because the importance scores of all resampling iterations were written to a single archive row (#168).
fix: fs("rfecv") ignored the direction of the measure and selected the feature set size with the worst mean performance for minimizing measures such as msr("classif.ce") or msr("regr.mse"). Feature selection results obtained with fs("rfecv") and a minimizing measure are invalid and should be recomputed (#167).

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("mlr3fselect", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("mlr-org/mlr3fselect")

Development version from mlr-org/mlr3fselect. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-mlr3fselect

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-mlr3fselect

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-mlr3fselect

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 10.4 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-30
ERROR10 OK, 3 ERROR2026-07-25
OK13 OK2026-05-28
ERROR12 OK, 1 ERROR2026-05-16
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.7.0

READMEYes · 744 wordsVignettesNoNEWSYes · 100% structured · mentions 1.7.0Citation fileYes · software entry onlyWebsiteYes · pkgdown

Help pages: 55 (4 internal)includes a package overview page
Examples that run: 47%14 run in a plain check (1 of them under a condition) · 16 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 50%
Documented parameters: 100%
Return-value docs: 21%
Help pages citing references: 2%

How these are measured

Downloads

62.5K

CRAN downloads in the past year

Rank #1,808 · ~171/day · ~5.2K/mo

Releases R versions

Daily download trend is not available in this view yet.

3.6K30 days

11.1K90 days

62.5K1 year

Compare downloads with other packages →

Also on2.8K r2u11 autocran3.7K conda_forge

How downloads are counted

Repository

mlr-org/mlr3fselect ↗Organization: mlr-org

43Stars

6Forks

3Open issues

0Open PRs

30Releases

781Commits

11Commit identities

machine-learningroptimizationfeature-selectionevolutionary-algorithmsrandom-searchexhaustive-searchrecursive-feature-elimination

License file reads as LGPL-3.0 · 781 commits · Last activity 2026-09-23 · 0% stars, 30d · Default branch at 1.7.0.9000, ahead of CRAN 1.7.0 (checked 2026-10-11) · Discussions: 4 posts

Responsiveness

How these are sampled

PRs merged (all time): 95%
Median days to close, 50 most recently updated closed issues: 3
Median days to close, 50 most recently updated closed PRs: 0

Stars over time

2025-09-06 · 362026-09-14 · 43

How these are measured

PracticesBeta

16 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/mlr-org/mlr3fselect on 2026-10-11.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, and on R-devel

Governance and community (3)

Contributing guide (inherited from mlr-org)

Funding links: GitHub Sponsors

The repository owner accepts GitHub Sponsors

Docs source (4)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-09-23 · The repository has a site deploy workflow

pkgdown site last built 2026-08-23

Automation and maintenance (1)

Dependabot

Show all practicesHide 2 practices

Lint, format, editor (5)

lintrAirEditorConfigVS CodeRStudio project

Git structural (1)

blame-ignore revs

How this is detected·Detection ruleset v3 (2026-09-26)

AI coding toolsBeta

This repository shows signs of AI coding tools.

Claude Codefirst seen 2026-03-17
Seen in the repository: .claude, CLAUDE.md
Named in .Rbuildignore: .claude, CLAUDE.md
Named in .gitignore: .claude, CLAUDE.md
Pull request it wrote: opened by a project member
Commits: at least 15 crediting it in the message
Cursorfirst seen 2026-03-18
Named in .Rbuildignore: .cursor
Gemini CLIfirst seen 2026-03-18
Config: a file or ignore line, not recorded which
Codexfirst seen 2026-09-23
Seen in the repository: .codex
Named in .Rbuildignore: .codex

Shared conventions any agent may read, so they name no particular tool.

Seen in the repository: AGENTS.md

Models named in its commits

Claude Opus 4.84 commits · Jul 2026
Claude Opus 54 commits · Jul to Sep 2026
Claude Opus 4.63 commits · Mar to May 2026
Claude Fable 52 commits · Jun 2026
Claude Opus 4.71 commit · Apr 2026

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

20 external dependencies (excludes base and recommended)

Installing mlr3fselect adds 30 packages (15 with compiled code, 20 MB of source tarballs). Heaviest: data.table 5.7 MB, palmerpenguins 2.9 MB, moocore 1.9 MB.

Depends (2)

R >= 3.1.0mlr3

Imports (9)

bbotk checkmate cli data.table lgr mlr3misc paradox R6 stabm

LinkingTo (0)

none

Suggests (11)

e1071 fastVoteR genalg mirai mlr3learners mlr3pipelines processx reduxrpartrush testthat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

2direct

1indirect

Imports 2

Suggested by 1

Depends, Imports or LinkingTo, most downloaded first

mlr3verse xplainfi

Suggests, most downloaded first

mlr3viz

How these are counted

Code & Tests

People & History

People (5)

Marc Becker

Author, Maintainer since 0.2.0 (2020)

Author

Author

Author

Author · added in 1.0.0

Releases (30)

Pick two releases to compare their code metrics.

1.7.0Latest
record
2026-08-23 · current release · diff ↗
1.6.0
record
2026-05-21 · diff ↗
R
R 4.6.0 released · 2026-04-24
1.5.1
record
2026-03-18 · diff ↗
1.5.0
record
2025-11-27 · diff ↗ ·
added 1 export
faggregate
1.4.0
record
2025-07-31 · diff ↗ ·
added 16 exports
ArchiveAsyncFSelect, ArchiveAsyncFSelectFrozen, CallbackAsyncFSelect, ContextAsyncFSelect, FSelectInstanceAsyncMultiCrit, FSelectInstanceAsyncSingleCrit, FSelectorAsync, FSelectorAsyncDesignPoints, FSelectorAsyncExhaustiveSearch, FSelectorAsyncFromOptimizerAsync, FSelectorAsyncRandomSearch, ObjectiveFSelectAsync, assert_async_fselect_callback, assert_async_fselect_callbacks, callback_async_fselect, fsi_async
R
R 4.5.0 released · 2025-04-11
1.3.0
record
2025-01-16 · diff ↗ ·
added 1 export
embedded_ensemble_fselect
1.2.1
record
2024-11-07 · diff ↗
1.2.0
record
2024-10-25 · diff ↗
1.1.1
record
2024-10-15 · diff ↗
1.1.0
record
2024-09-09 · diff ↗
1.0.0
record
2024-06-29 · diff ↗ ·
removed 14 exports
ArchiveFSelect, ContextEval, FSelectInstanceMultiCrit, FSelectInstanceSingleCrit, FSelectorDesignPoints, FSelectorExhaustiveSearch, FSelectorFromOptimizer, FSelectorGeneticSearch, FSelectorRFE, FSelectorRFECV, FSelectorRandomSearch, FSelectorSequential, FSelectorShadowVariableSearch, callback_fselect

added 24 exports
ArchiveBatchFSelect, ContextBatchFSelect, EnsembleFSResult, FSelectInstanceBatchMultiCrit, FSelectInstanceBatchSingleCrit, FSelectorBatch, FSelectorBatchDesignPoints, FSelectorBatchExhaustiveSearch, FSelectorBatchFromOptimizerBatch, FSelectorBatchGeneticSearch, FSelectorBatchRFE, FSelectorBatchRFECV, FSelectorBatchRandomSearch, FSelectorBatchSequential, FSelectorBatchShadowVariableSearch, ObjectiveFSelectBatch, assert_fselect_instance, assert_fselect_instance_async, assert_fselect_instance_batch, assert_fselector_async, assert_fselector_batch, assert_fselectors, callback_batch_fselect, ensemble_fselect
R
R 4.4.0 released · 2024-04-24
0.12.0
record
2024-03-09 · diff ↗
R
R 4.3.0 released · 2023-04-21

Show 21 earlier eventsHide 21 earlier events

0.11.0
record
2023-03-02 · diff ↗
0.10.0
record
2023-02-21 · diff ↗ ·
added 1 export
FSelectorRFECV
0.9.1
record
2023-01-26 · diff ↗
0.9.0
record
2022-12-21 · diff ↗ ·
added 5 exports
ContextEval, callback_fselect, clbk, clbks, mlr_callbacks
0.8.1
record
2022-11-27 · diff ↗
0.8.0
record
2022-11-16 · diff ↗ ·
added 1 export
fsi
0.7.2
record
2022-08-25 · diff ↗
0.7.1
record
2022-05-03 · diff ↗
R
R 4.2.0 released · 2022-04-22
0.7.0
record
2022-04-08 · diff ↗
0.6.1
record
2022-01-20 · diff ↗
0.6.0
record
2021-09-13 · diff ↗ ·
added 7 exports
FSelectorShadowVariableSearch, auto_fselector, extract_inner_fselect_archives, extract_inner_fselect_results, fselect, fselect_nested, fss
R
R 4.1.0 released · 2021-05-18
0.5.1
record
2021-03-09 · diff ↗
0.5.0
record
2021-01-24 · diff ↗
0.4.1
record
2020-10-30 · diff ↗
0.4.0
record
2020-10-22 · diff ↗ ·
removed 1 export
AutoFSelect

added 3 exports
AutoFSelector, FSelectorGeneticSearch, trms
0.3.0
record
2020-09-22 · diff ↗ ·
added 1 export
ArchiveFSelect
0.2.1
record
2020-09-10 · diff ↗
0.2.0
record
2020-08-23
R
R 4.0.0 released · 2020-04-24

Package metadata

First published: 2020-08-23
Total releases: 30 / 6 yrs
License: LGPL-3 OSI
Minimum R: ≥ 3.1.0
Download size: 174 KB

Cite

Cite this package

Run in R for the authors' entry:

citation("mlr3fselect")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.5281/zenodo.16673301.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mlr3fselect version 1.7.0 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →