This package is considered a duplicate. The official version of this package is found at:https://mlr-org.r-universe.dev/mlr3fselect

Package: mlr3fselect 1.2.1

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_1.2.1.tar.gz
mlr3fselect_1.2.1.tar.gz(r-4.5-noble)mlr3fselect_1.2.1.tar.gz(r-4.4-noble)
mlr3fselect_1.2.1.tgz(r-4.4-emscripten)mlr3fselect_1.2.1.tgz(r-4.3-emscripten)
mlr3fselect.pdf |mlr3fselect.html✨
mlr3fselect/json (API)
NEWS

# Install 'mlr3fselect' in R:

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

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

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

4.62 score 2 packages 64 scripts 3.6k downloads 42 exports 25 dependencies

Last updated 2 months agofrom:fd47ac02ca. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 08 2024
R-4.5-linux	OK	Dec 08 2024

Exports:ArchiveBatchFSelect assert_fselect_instance assert_fselect_instance_async assert_fselect_instance_batch assert_fselector_async assert_fselector_batch assert_fselectors auto_fselector AutoFSelector callback_batch_fselect clbk clbks ContextBatchFSelect ensemble_fselect EnsembleFSResult extract_inner_fselect_archives extract_inner_fselect_results fs fselect fselect_nested FSelectInstanceBatchMultiCrit FSelectInstanceBatchSingleCrit FSelector FSelectorBatch FSelectorBatchDesignPoints FSelectorBatchExhaustiveSearch FSelectorBatchFromOptimizerBatch FSelectorBatchGeneticSearch FSelectorBatchRandomSearch FSelectorBatchRFE FSelectorBatchRFECV FSelectorBatchSequential FSelectorBatchShadowVariableSearch fsi fss mlr_callbacks mlr_fselectors mlr_terminators ObjectiveFSelect ObjectiveFSelectBatch trm trms

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

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Readme and manuals

Help Manual

Help page	Topics
mlr3fselect: Feature Selection for 'mlr3'	mlr3fselect-package mlr3fselect
Class for Logging Evaluated Feature Sets	ArchiveBatchFSelect
Function for Automatic Feature Selection	auto_fselector
Class for Automatic Feature Selection	AutoFSelector
Create Feature Selection Callback	callback_batch_fselect
Create Feature Selection Callback	CallbackBatchFSelect
Evaluation Context	ContextBatchFSelect
Ensemble Feature Selection Result	EnsembleFSResult ensemble_fs_result
Ensemble Feature Selection	ensemble_fselect
Extract Inner Feature Selection Archives	extract_inner_fselect_archives
Extract Inner Feature Selection Results	extract_inner_fselect_results
Syntactic Sugar for FSelect Construction	fs fss
Function for Feature Selection	fselect
Function for Nested Resampling	fselect_nested
Class for Multi Criteria Feature Selection	FSelectInstanceBatchMultiCrit
Class for Single Criterion Feature Selection	FSelectInstanceBatchSingleCrit
FSelector	FSelector
Class for Batch Feature Selection Algorithms	FSelectorBatch
Syntactic Sugar for Instance Construction	fsi
Dictionary of FSelectors	mlr_fselectors
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
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	ObjectiveFSelectBatch

Package: mlr3fselect 1.2.1

mlr3fselect: Feature Selection for 'mlr3'

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)