Extract Inner Feature Selection Archives
Source:R/extract_inner_fselect_archives.R
extract_inner_fselect_archives.Rd
Extract inner feature selection archives of nested resampling.
Implemented for mlr3::ResampleResult and mlr3::BenchmarkResult.
The function iterates over the AutoFSelector objects and binds the archives to a data.table::data.table()
.
AutoFSelector must be initialized with store_fselect_instance = TRUE
and resample()
or benchmark()
must be called with store_models = TRUE
.
Arguments
- x
- exclude_columns
(
character()
)
Exclude columns from result table. Set toNULL
if no column should be excluded.
Data structure
The returned data table has the following columns:
experiment
(integer(1))
Index, giving the according row number in the original benchmark grid.iteration
(integer(1))
Iteration of the outer resampling.One column for each feature of the task.
One column for each performance measure.
runtime_learners
(numeric(1)
)
Sum of training and predict times logged in learners per mlr3::ResampleResult / evaluation. This does not include potential overhead time.timestamp
(POSIXct
)
Time stamp when the evaluation was logged into the archive.batch_nr
(integer(1)
)
Feature sets are evaluated in batches. Each batch has a unique batch number.resample_result
(mlr3::ResampleResult)
Resample result of the inner resampling.task_id
(character(1)
).learner_id
(character(1)
).resampling_id
(character(1)
).
Examples
# Nested Resampling on Palmer Penguins Data Set
# create auto fselector
at = auto_fselector(
fselector = fs("random_search"),
learner = lrn("classif.rpart"),
resampling = rsmp ("holdout"),
measure = msr("classif.ce"),
term_evals = 4)
resampling_outer = rsmp("cv", folds = 2)
rr = resample(tsk("penguins"), at, resampling_outer, store_models = TRUE)
# extract inner archives
extract_inner_fselect_archives(rr)
#> iteration bill_depth bill_length body_mass flipper_length island sex
#> <int> <lgcl> <lgcl> <lgcl> <lgcl> <lgcl> <lgcl>
#> 1: 1 TRUE TRUE TRUE FALSE TRUE FALSE
#> 2: 1 FALSE FALSE FALSE FALSE FALSE FALSE
#> 3: 1 TRUE TRUE TRUE TRUE TRUE FALSE
#> 4: 1 TRUE TRUE TRUE TRUE TRUE TRUE
#> 5: 1 FALSE FALSE TRUE FALSE FALSE FALSE
#> 6: 1 TRUE FALSE TRUE FALSE FALSE TRUE
#> 7: 1 FALSE TRUE TRUE TRUE TRUE FALSE
#> 8: 1 TRUE TRUE TRUE TRUE TRUE FALSE
#> 9: 1 FALSE TRUE FALSE FALSE TRUE TRUE
#> 10: 1 FALSE TRUE TRUE TRUE TRUE TRUE
#> 11: 2 FALSE FALSE TRUE TRUE FALSE TRUE
#> 12: 2 TRUE TRUE TRUE TRUE TRUE TRUE
#> 13: 2 FALSE FALSE FALSE FALSE TRUE FALSE
#> 14: 2 FALSE FALSE FALSE TRUE FALSE FALSE
#> 15: 2 TRUE TRUE TRUE TRUE TRUE TRUE
#> 16: 2 TRUE TRUE TRUE TRUE TRUE TRUE
#> 17: 2 TRUE TRUE TRUE TRUE TRUE TRUE
#> 18: 2 TRUE TRUE TRUE TRUE TRUE TRUE
#> 19: 2 FALSE TRUE TRUE FALSE FALSE FALSE
#> 20: 2 TRUE TRUE TRUE TRUE TRUE TRUE
#> iteration bill_depth bill_length body_mass flipper_length island sex
#> year classif.ce runtime_learners timestamp batch_nr warnings
#> <lgcl> <num> <num> <POSc> <int> <int>
#> 1: TRUE 0.07017544 0.005 2024-11-07 21:47:32 1 0
#> 2: TRUE 0.64912281 0.004 2024-11-07 21:47:32 1 0
#> 3: TRUE 0.05263158 0.006 2024-11-07 21:47:32 1 0
#> 4: FALSE 0.05263158 0.005 2024-11-07 21:47:32 1 0
#> 5: TRUE 0.36842105 0.005 2024-11-07 21:47:32 1 0
#> 6: FALSE 0.40350877 0.006 2024-11-07 21:47:32 1 0
#> 7: TRUE 0.05263158 0.005 2024-11-07 21:47:32 1 0
#> 8: TRUE 0.05263158 0.005 2024-11-07 21:47:32 1 0
#> 9: TRUE 0.07017544 0.006 2024-11-07 21:47:32 1 0
#> 10: TRUE 0.05263158 0.006 2024-11-07 21:47:32 1 0
#> 11: TRUE 0.26315789 0.006 2024-11-07 21:47:32 1 0
#> 12: TRUE 0.07017544 0.005 2024-11-07 21:47:32 1 0
#> 13: FALSE 0.36842105 0.004 2024-11-07 21:47:32 1 0
#> 14: FALSE 0.26315789 0.005 2024-11-07 21:47:32 1 0
#> 15: TRUE 0.07017544 0.007 2024-11-07 21:47:32 1 0
#> 16: TRUE 0.07017544 0.007 2024-11-07 21:47:32 1 0
#> 17: TRUE 0.07017544 0.005 2024-11-07 21:47:32 1 0
#> 18: FALSE 0.07017544 0.005 2024-11-07 21:47:32 1 0
#> 19: FALSE 0.05263158 0.005 2024-11-07 21:47:32 1 0
#> 20: TRUE 0.07017544 0.005 2024-11-07 21:47:32 1 0
#> year classif.ce runtime_learners timestamp batch_nr warnings
#> errors features
#> <int> <list>
#> 1: 0 bill_depth,bill_length,body_mass,island,year
#> 2: 0 year
#> 3: 0 bill_depth,bill_length,body_mass,flipper_length,island,year
#> 4: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex
#> 5: 0 body_mass,year
#> 6: 0 bill_depth,body_mass,sex
#> 7: 0 bill_length,body_mass,flipper_length,island,year
#> 8: 0 bill_depth,bill_length,body_mass,flipper_length,island,year
#> 9: 0 bill_length,island,sex,year
#> 10: 0 bill_length,body_mass,flipper_length,island,sex,year
#> 11: 0 body_mass,flipper_length,sex,year
#> 12: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex,...
#> 13: 0 island
#> 14: 0 flipper_length
#> 15: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex,...
#> 16: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex,...
#> 17: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex,...
#> 18: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex
#> 19: 0 bill_length,body_mass
#> 20: 0 bill_depth,bill_length,body_mass,flipper_length,island,sex,...
#> errors features
#> n_features resample_result task_id learner_id resampling_id
#> <list> <list> <char> <char> <char>
#> 1: 5 <ResampleResult> penguins classif.rpart.fselector cv
#> 2: 1 <ResampleResult> penguins classif.rpart.fselector cv
#> 3: 6 <ResampleResult> penguins classif.rpart.fselector cv
#> 4: 6 <ResampleResult> penguins classif.rpart.fselector cv
#> 5: 2 <ResampleResult> penguins classif.rpart.fselector cv
#> 6: 3 <ResampleResult> penguins classif.rpart.fselector cv
#> 7: 5 <ResampleResult> penguins classif.rpart.fselector cv
#> 8: 6 <ResampleResult> penguins classif.rpart.fselector cv
#> 9: 4 <ResampleResult> penguins classif.rpart.fselector cv
#> 10: 6 <ResampleResult> penguins classif.rpart.fselector cv
#> 11: 4 <ResampleResult> penguins classif.rpart.fselector cv
#> 12: 7 <ResampleResult> penguins classif.rpart.fselector cv
#> 13: 1 <ResampleResult> penguins classif.rpart.fselector cv
#> 14: 1 <ResampleResult> penguins classif.rpart.fselector cv
#> 15: 7 <ResampleResult> penguins classif.rpart.fselector cv
#> 16: 7 <ResampleResult> penguins classif.rpart.fselector cv
#> 17: 7 <ResampleResult> penguins classif.rpart.fselector cv
#> 18: 6 <ResampleResult> penguins classif.rpart.fselector cv
#> 19: 2 <ResampleResult> penguins classif.rpart.fselector cv
#> 20: 7 <ResampleResult> penguins classif.rpart.fselector cv
#> n_features resample_result task_id learner_id resampling_id