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$result
.
- feat: Add
ties_method
options
"least_features"
and "random"
to
ArchiveBatchFSelect$best()
.
- refactor: Optimize runtime of
ArchiveBatchFSelect$best()
method.
- feat: Add importance scores to result of
FSelectorRFE
.
- feat: Add number of features to
as.data.table.ArchiveBatchFSelect()
.
- 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
FSelectorBatchRandomSearch
to 10.
- feat: Add
batch_size
parameter to
FSelectorBatchExhaustiveSearch
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.ArchiveBatchFSelect()
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
FSelectorBatchGeneticSearch
.
- feat: Add new callback that backups the benchmark result to disk
after each batch.
- feat: Create custom callbacks with the
callback_batch_fselect()
function.
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
FSelectInstanceBatchSingleCrit
or
FSelectInstanceBatchMultiCrit
.
- refactor: Remove
unnest
option from
as.data.table.ArchiveBatchFSelect()
function.
mlr3fselect 0.7.2
- docs: Re-generate rd files with valid html.
mlr3fselect 0.7.1
- feat:
FSelector
objects have the field $id
now.
mlr3fselect 0.7.0
- feat: Allow to pass
FSelector
objects as
method
in fselect()
and
auto_fselector()
.
- feat: Added
$label
to FSelector
s.
- docs: New examples with
fselect()
function.
- feat:
$help()
method which opens manual page of a
FSelector
.
- feat: Added a
as.data.table.DictionaryFSelector
function.
- feat: Added
min_features
parameter to
FSelectorBatchSequential
.
mlr3fselect 0.6.1
- Add
store_models
flag to fselect()
.
- Remove
store_x_domain
flag.
mlr3fselect 0.6.0
- Adds
AutoFSelector$base_learner()
method to extract the
base learner from nested learner objects.
- Adds
fselect()
, auto_fselector()
and
fselect_nested()
sugar functions.
- Adds
extract_inner_fselect_results()
and
extract_inner_fselect_archives()
helper function to extract
inner feature selection results and archives.
mlr3fselect 0.5.1
- Remove
x_domain
column from archive.
mlr3fselect 0.5.0
FSelectorRFE
stores importance values of each evaluated
feature set in archive.
ArchiveBatchFSelect$data
is a public field now.
mlr3fselect 0.4.1
- Fix bug in
AutoFSelector$predict()
mlr3fselect 0.4.0
- Compact in-memory representation of R6 objects to save space when
saving mlr3 objects via saveRDS(), serialize() etc.
FSelectorRFE
supports fraction of features to retain in
each iteration (feature_fraction
), number of features to
remove in each iteration (feature_number
) and vector of
number of features to retain in each iteration
(subset_sizes
).
AutoFSelect
is renamed to
AutoFSelector
.
- To retrieve the inner feature selection results in nested
resampling,
as.data.table(rr)$learner[[1]]$fselect_result
must be used now.
- Option to control
store_benchmark_result
,
store_models
and check_values
in
AutoFSelector
. store_fselect_instance
must be
set as a parameter during initialization.
- Adds
FSelectorBatchGeneticSearch
.
- Fixes
check_values
flag in
FSelectInstanceBatchSingleCrit
and
FSelectInstanceBatchMultiCrit
.
- Removed dependency on orphaned package
bibtex
.
PipeOpSelect
is internally used for task
subsetting.
mlr3fselect 0.3.0
Archive
is ArchiveBatchFSelect
now which
stores the benchmark result in $benchmark_result
. This
change removed the resample results from the archive but they can be
still accessed via the benchmark result.
mlr3fselect 0.2.1
- Warning message if external package for feature selection is not
installed.
mlr3fselect 0.2.0