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'))

Peer review:

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

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

4.60 score 2 packages 59 scripts 3.8k downloads 42 exports 25 dependencies

Last updated 30 days agofrom:fd47ac02ca. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-linuxOKNov 08 2024

Exports:ArchiveBatchFSelectassert_fselect_instanceassert_fselect_instance_asyncassert_fselect_instance_batchassert_fselector_asyncassert_fselector_batchassert_fselectorsauto_fselectorAutoFSelectorcallback_batch_fselectclbkclbksContextBatchFSelectensemble_fselectEnsembleFSResultextract_inner_fselect_archivesextract_inner_fselect_resultsfsfselectfselect_nestedFSelectInstanceBatchMultiCritFSelectInstanceBatchSingleCritFSelectorFSelectorBatchFSelectorBatchDesignPointsFSelectorBatchExhaustiveSearchFSelectorBatchFromOptimizerBatchFSelectorBatchGeneticSearchFSelectorBatchRandomSearchFSelectorBatchRFEFSelectorBatchRFECVFSelectorBatchSequentialFSelectorBatchShadowVariableSearchfsifssmlr_callbacksmlr_fselectorsmlr_terminatorsObjectiveFSelectObjectiveFSelectBatchtrmtrms

Dependencies:backportsbbotkcheckmatecodetoolsdata.tabledigestevaluatefuturefuture.applyglobalslatticelgrlistenvMatrixmlbenchmlr3mlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6stabmuuid

Readme and manuals

Help Manual

Help pageTopics
mlr3fselect: Feature Selection for 'mlr3'mlr3fselect-package mlr3fselect
Class for Logging Evaluated Feature SetsArchiveBatchFSelect
Function for Automatic Feature Selectionauto_fselector
Class for Automatic Feature SelectionAutoFSelector
Create Feature Selection Callbackcallback_batch_fselect
Create Feature Selection CallbackCallbackBatchFSelect
Evaluation ContextContextBatchFSelect
Ensemble Feature Selection ResultEnsembleFSResult ensemble_fs_result
Ensemble Feature Selectionensemble_fselect
Extract Inner Feature Selection Archivesextract_inner_fselect_archives
Extract Inner Feature Selection Resultsextract_inner_fselect_results
Syntactic Sugar for FSelect Constructionfs fss
Function for Feature Selectionfselect
Function for Nested Resamplingfselect_nested
Class for Multi Criteria Feature SelectionFSelectInstanceBatchMultiCrit
Class for Single Criterion Feature SelectionFSelectInstanceBatchSingleCrit
FSelectorFSelector
Class for Batch Feature Selection AlgorithmsFSelectorBatch
Syntactic Sugar for Instance Constructionfsi
Dictionary of FSelectorsmlr_fselectors
Feature Selection with Design PointsFSelectorBatchDesignPoints mlr_fselectors_design_points
Feature Selection with Exhaustive SearchFSelectorBatchExhaustiveSearch mlr_fselectors_exhaustive_search
Feature Selection with Genetic SearchFSelectorBatchGeneticSearch mlr_fselectors_genetic_search
Feature Selection with Random SearchFSelectorBatchRandomSearch mlr_fselectors_random_search
Feature Selection with Recursive Feature EliminationFSelectorBatchRFE mlr_fselectors_rfe
Feature Selection with Recursive Feature Elimination with Cross ValidationFSelectorBatchRFECV mlr_fselectors_rfecv
Feature Selection with Sequential SearchFSelectorBatchSequential mlr_fselectors_sequential
Feature Selection with Shadow Variable SearchFSelectorBatchShadowVariableSearch mlr_fselectors_shadow_variable_search
Backup Benchmark Result Callbackmlr3fselect.backup
Internal Tuning Callbackmlr3fselect.internal_tuning
One Standard Error Rule Callbackmlr3fselect.one_se_rule
SVM-RFE Callbackmlr3fselect.svm_rfe
Class for Feature Selection ObjectiveObjectiveFSelect
Class for Feature Selection ObjectiveObjectiveFSelectBatch