mlr3 package updates – Q4/2021

Machine Learning in R

2 months ago

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Due to the high amount of packages in the mlr3 ecosystem, it is hard to keep up with the latest changes across all packages. This posts gives an overview by listing the recent release notes of mlr3 packages from the last quarter. Note that only CRAN packages are listed here and the sort order is alphabetically.

Interval: 2021-10-01 – 2021-12-31

mlr3 0.13.0 – https://github.com/mlr-org/mlr3

Description: Machine Learning in R – Next Generation

Learners which are capable of resuming/continuing (e.g., learner (classif|regr|surv).xgboost with hyperparameter nrounds updated) can now optionally store a stack of trained learners to be used to hotstart their training. Note that this feature is still somewhat experimental. See HotstartStack and #719.
New measures to score similarity of selected feature sets: sim.jaccard (Jaccard Index) and sim.phi (Phi coefficient) (#690).
predict_newdata() now also supports DataBackend as input.
New function install_pkgs() to install required packages. This generic works for all objects with a packages field as well as ResampleResult and BenchmarkResult (#728).
New learner regr.debug for debugging.
New Task method $set_levels() to control how data with factor columns is returned, independent of the used DataBackend.
Measures now return NA if prerequisite are not met (#699). This allows to conveniently score your experiments with multiple measures having different requirements.
Feature names may no longer contain the special character %.

mlr3benchmark 0.1.3 – https://github.com/mlr-org/mlr3benchmark

Description: Analysis and Visualisation of Benchmark Experiments

Fix README.
Fix for PMCMRplus.

mlr3db 0.4.2 – https://github.com/mlr-org/mlr3db

Description: Data Base Backend for ‘mlr3’

Compatibility fixes with new duckdb version.

mlr3learners 0.5.1- – https://github.com/mlr-org/mlr3learners

Description: Recommended learners for mlr3

eval_metric() is now explicitly set for xgboost learners to silence a deprecation warning.
Improved how the added hyperparameter mtry.ratio is converted to mtry to simplify tuning.
Multiple updates to hyperparameter sets.

mlr3pipelines 0.4.0 – https://github.com/mlr-org/mlr3pipelines

Description: Preprocessing Operators and Pipelines for ‘mlr3’

New operator %>>!% that modifies Graphs in-place.
New methods chain_graphs(), concat_graphs(), Graph$chain() as alternatives for %>>% and %>>!%.
New methods pos() and ppls() which create lists of PipeOps/Graphs and can be seen as “plural” forms of po() and ppl().
po() S3-method for PipeOp class that clones a PipeOp object and optionally modifies its attributes.
Graph$add_pipeop() now clones the PipeOp being added.
Documentation: Clarified documentation about cloning of input arguments in several places.
Performance enhancements for Graph concatenation.
More informative error outputs.
New attribute graph_model GraphLearner class, which gets the trained graph.
as_learner() S3-method for PipeOp class that turns wraps a PipeOp in a Graph and turns that into a Learner.
Changed PipeOps:
- PipeOpHistBin: renamed ‘bins’ Param to ‘breaks’
- PipeOpImputeHist: fix handling of integer features spanning the entire represented integer range
- PipeOpImputeOOR: fix handling of integer features spanning the entire represented integer range
- PipeOpProxy: Avoid unnecessary clone
- PipeOpScale: Performance improvement