Package: mlr3fselect 1.5.1

Marc Becker

mlr3fselect: Feature Selection for 'mlr3'

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.

Authors:Marc Becker [aut, cre], Patrick Schratz [aut], Michel Lang [aut], Bernd Bischl [aut], John Zobolas [aut]

mlr3fselect_1.5.1.tar.gz
mlr3fselect_1.5.1.zip(r-4.7)mlr3fselect_1.5.1.zip(r-4.6)mlr3fselect_1.5.1.zip(r-4.5)
mlr3fselect_1.5.1.tgz(r-4.6-any)mlr3fselect_1.5.1.tgz(r-4.5-any)
mlr3fselect_1.5.1.tar.gz(r-4.7-any)mlr3fselect_1.5.1.tar.gz(r-4.6-any)
mlr3fselect_1.5.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mlr3fselect/json (API)
NEWS

# Install 'mlr3fselect' in R:

install.packages('mlr3fselect', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mlr-org/mlr3fselect/issues

Pkgdown/docs site:https://mlr3fselect.mlr-org.com

On CRAN:

evolutionary-algorithms exhaustive-search feature-selection machine-learning mlr3 optimization random-search recursive-feature-elimination sequential-feature-selection

9.14 score 40 stars 3 packages 133 scripts 6.0k downloads 60 exports 29 dependencies

Last updated from:70f2d9d811 (on v1.5.1). Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	332
source / vignettes	OK	207
linux-release-x86_64	OK	332
macos-release-arm64	OK	191
macos-oldrel-arm64	OK	252
windows-devel	OK	462
windows-release	OK	385
windows-oldrel	OK	326
wasm-release	OK	116

Exports:ArchiveAsyncFSelect ArchiveAsyncFSelectFrozen ArchiveBatchFSelect assert_async_fselect_callback assert_async_fselect_callbacks assert_fselect_instance assert_fselect_instance_async assert_fselect_instance_batch assert_fselector_async assert_fselector_batch assert_fselectors auto_fselector AutoFSelector callback_async_fselect callback_batch_fselect CallbackAsyncFSelect clbk clbks ContextAsyncFSelect ContextBatchFSelect embedded_ensemble_fselect ensemble_fselect EnsembleFSResult extract_inner_fselect_archives extract_inner_fselect_results faggregate fs fselect fselect_nested FSelectInstanceAsyncMultiCrit FSelectInstanceAsyncSingleCrit FSelectInstanceBatchMultiCrit FSelectInstanceBatchSingleCrit FSelector FSelectorAsync FSelectorAsyncDesignPoints FSelectorAsyncExhaustiveSearch FSelectorAsyncFromOptimizerAsync FSelectorAsyncRandomSearch FSelectorBatch FSelectorBatchDesignPoints FSelectorBatchExhaustiveSearch FSelectorBatchFromOptimizerBatch FSelectorBatchGeneticSearch FSelectorBatchRandomSearch FSelectorBatchRFE FSelectorBatchRFECV FSelectorBatchSequential FSelectorBatchShadowVariableSearch fsi fsi_async fss mlr_callbacks mlr_fselectors mlr_terminators ObjectiveFSelect ObjectiveFSelectAsync ObjectiveFSelectBatch trm trms

Dependencies:backports bbotk checkmate cli codetools data.table digest evaluate future future.apply globals lattice lgr listenv Matrix mirai mlbench mlr3 mlr3measures mlr3misc nanonext palmerpenguins paradox parallelly PRROC R6 rlang stabm uuid

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
mlr3fselect: Feature Selection for 'mlr3'	mlr3fselect-package mlr3fselect
Rush Data Storage	ArchiveAsyncFSelect
Frozen Rush Data Storage	ArchiveAsyncFSelectFrozen
Class for Logging Evaluated Feature Sets	ArchiveBatchFSelect
Assertions for Callbacks	assert_async_fselect_callback assert_async_fselect_callbacks
Function for Automatic Feature Selection	auto_fselector
Class for Automatic Feature Selection	AutoFSelector
Create Asynchronous Feature Selection Callback	callback_async_fselect
Create Feature Selection Callback	callback_batch_fselect
Asynchronous Feature Selection Callback	CallbackAsyncFSelect
Create Feature Selection Callback	CallbackBatchFSelect
Asynchronous Feature Selection Context	ContextAsyncFSelect
Evaluation Context	ContextBatchFSelect
Embedded Ensemble Feature Selection	embedded_ensemble_fselect
Ensemble Feature Selection Result	EnsembleFSResult ensemble_fs_result
Wrapper-based Ensemble Feature Selection	ensemble_fselect
Extract Inner Feature Selection Archives	extract_inner_fselect_archives
Extract Inner Feature Selection Results	extract_inner_fselect_results
Fast Aggregation of ResampleResults and BenchmarkResults	faggregate
Syntactic Sugar for Feature Selection Objects Construction	fs fss
Function for Feature Selection	fselect
Function for Nested Resampling	fselect_nested
Multi-Criteria Feature Selection with Rush	FSelectInstanceAsyncMultiCrit
Single Criterion Feature Selection with Rush	FSelectInstanceAsyncSingleCrit
Class for Multi Criteria Feature Selection	FSelectInstanceBatchMultiCrit
Class for Single Criterion Feature Selection	FSelectInstanceBatchSingleCrit
FSelector	FSelector
Class for Asynchronous Feature Selection Algorithms	FSelectorAsync
Class for Batch Feature Selection Algorithms	FSelectorBatch
Syntactic Sugar for Feature Selection Instance Construction	fsi
Syntactic Sugar for Asynchronous Feature Selection Instance Construction	fsi_async
Dictionary of FSelectors	mlr_fselectors
Feature Selection with Asynchronous Design Points	FSelectorAsyncDesignPoints mlr_fselectors_async_design_points
Feature Selection with Asynchronous Exhaustive Search	FSelectorAsyncExhaustiveSearch mlr_fselectors_async_exhaustive_search
Feature Selection with Asynchronous Random Search	FSelectorAsyncRandomSearch mlr_fselectors_async_random_search
Feature Selection with Design Points	FSelectorBatchDesignPoints mlr_fselectors_design_points
Feature Selection with Exhaustive Search	FSelectorBatchExhaustiveSearch mlr_fselectors_exhaustive_search
Feature Selection with Genetic Search	FSelectorBatchGeneticSearch mlr_fselectors_genetic_search
Feature Selection with Random Search	FSelectorBatchRandomSearch mlr_fselectors_random_search
Feature Selection with Recursive Feature Elimination	FSelectorBatchRFE mlr_fselectors_rfe
Feature Selection with Recursive Feature Elimination with Cross Validation	FSelectorBatchRFECV mlr_fselectors_rfecv
Feature Selection with Sequential Search	FSelectorBatchSequential mlr_fselectors_sequential
Feature Selection with Shadow Variable Search	FSelectorBatchShadowVariableSearch mlr_fselectors_shadow_variable_search
Freeze Archive Callback	mlr3fselect.async_freeze_archive
Backup Benchmark Result Callback	mlr3fselect.backup
Internal Tuning Callback	mlr3fselect.internal_tuning
One Standard Error Rule Callback	mlr3fselect.one_se_rule
SVM-RFE Callback	mlr3fselect.svm_rfe
Class for Feature Selection Objective	ObjectiveFSelect
Class for Feature Selection Objective	ObjectiveFSelectAsync
Class for Feature Selection Objective	ObjectiveFSelectBatch