mlr3fselect 1.1.0

• compatibility: mlr3 0.21.0
• fix: Delete intermediate BenchmarkResult in ObjectiveFSelectBatch after optimization.
• fix: Reloading mlr3fselect does not duplicate column roles anymore.
• perf: Remove x_domain column from archive.

mlr3fselect 1.0.0

• feat: Add ensemble feature selection function ensemble_fselect().
• BREAKING CHANGE: The FSelector class is FSelectorBatch now.
• BREAKING CHANGE: THe FSelectInstanceSingleCrit and FSelectInstanceMultiCrit classes are FSelectInstanceBatchSingleCrit and FSelectInstanceBatchMultiCrit now.
• BREAKING CHANGE: The CallbackFSelect class is CallbackBatchFSelect now.
• BREAKING CHANGE: The ContextEval class is ContextBatchFSelect now.

mlr3fselect 0.12.0

• feat: Add number of features to instance$result.
• feat: Add ties_method options "least_features" and "random" to ArchiveFSelect$best().
• refactor: Optimize runtime of ArchiveFSelect$best() method.
• feat: Add importance scores to result of FSelectorRFE.
• feat: Add number of features to as.data.table.ArchiveFSelect().
• feat: Features can be always included with the always_include column role.
• fix: Add $phash() method to AutoFSelector.
• fix: Include FSelector in hash of AutoFSelector.
• refactor: Change default batch size of FSelectorRandomSearch to 10.
• feat: Add batch_size parameter to FSelectorExhaustiveSearch to reduce memory consumption.
• compatibility: Work with new paradox version 1.0.0

mlr3fselect 0.11.0

• BREAKING CHANGE: The method parameter of fselect(), fselect_nested() and auto_fselector() is renamed to fselector.
  Only FSelector objects are accepted now.
  Arguments to the fselector cannot be passed with ... anymore.
• BREAKING CHANGE: The fselect parameter of FSelector is moved to the first position to achieve consistency with the other functions.
• docs: Update resources sections.
• docs: Add list of default measures.

mlr3fselect 0.10.0

• feat: Add callback mlr3fselect.svm_rfe to run recursive feature elimination on linear support vector machines.
• refactor: The importance scores in FSelectorRFE are now aggregated by rank instead of averaging them.
• feat: Add FSelectorRFECV optimizer to run recursive feature elimination with cross-validation.
• refactor: FSelectorRFE works without store_models = TRUE now.
• feat: The as.data.table.ArchiveFSelect() function additionally returns a character vector of selected features for each row.
• refactor: Add callbacks argument to fsi() function.

mlr3fselect 0.9.1

• refactor: Remove internal use of mlr3pipelines.
• fix: Feature selection with measures that require the importance or oob error works now.

mlr3fselect 0.9.0

• fix: Add genalg to required packages of FSelectorGeneticSearch.
• feat: Add new callback that backups the benchmark result to disk after each batch.
• feat: Create custom callbacks with the callback_fselect() function.

mlr3fselect 0.8.1

• fix: Add genalg to required packages of FSelectorGeneticSearch.

mlr3fselect 0.8.0

• refactor: FSelectorRFE throws an error if the learner does not support the $importance() method.
• refactor: The AutoFSelector stores the instance and benchmark result if store_models = TRUE.
• refactor: The AutoFSelector stores the instance if store_benchmark_result = TRUE.
• feat: Add missing parameters from AutoFSelector to auto_fselect().
• feat: Add fsi() function to create a FSelectInstanceSingleCrit or FSelectInstanceMultiCrit.
• refactor: Remove unnest option from as.data.table.ArchiveFSelect() function.

mlr3fselect 0.7.2

• docs: Re-generate rd files with valid html.