Tags: MichaelChirico/mlr
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mlr 2.19.1.9000 ## Continuous integration - Only build on r-devel - Add fledge support ## precommit - Skip styler hook due to timeout - Remove roxygenize hook ## CPPFLAGS - Suppress unused arguments warning ## Uncategorized - Consistent naming for dummy feature encoding of variables with different levels count (mlr-org#2847) - Remove nodeHarvest learners (mlr-org#2841) - Remove rknn learner (mlr-org#2842) - Remove all {DiscriMiner} learners (mlr-org#2840) - Remove extraTrees learner (mlr-org#2839) - [github.com/lorenzwalthert/precommit: v0.3.0 → v0.3.2](lorenzwalthert/precommit@v0.3.0...v0.3.2) (@66853113+pre-commit-ci[bot], mlr-org#2838) - [github.com/pre-commit/pre-commit-hooks: v4.2.0 → v4.3.0](pre-commit/pre-commit-hooks@v4.2.0...v4.3.0) (@66853113+pre-commit-ci[bot], mlr-org#2838) - [github.com/lorenzwalthert/precommit: v0.2.2.9015 → v0.3.0](lorenzwalthert/precommit@v0.2.2.9015...v0.3.0) (@66853113+pre-commit-ci[bot], mlr-org#2835) - R 4.2 fixes (mlr-org#2823) - Remove depcrecated rrlda learner - Resolve some ggplot deprecation warnings
mlr 2.19.1 ## Bug fixes - Adjust behavior of `"positive"` arg for `classif.logreg` (mlr-org#2846) - Consistent naming for dummy feature encoding of variables with different levels count (mlr-org#2847) - Remove {nodeHarvest} learners (mlr-org#2841) - Remove {rknn} learner (mlr-org#2842) - Remove all {DiscriMiner} learners (mlr-org#2840) - Remove {extraTrees} learner (mlr-org#2839) - Remove depcrecated {rrlda} learner - Resolve some {ggplot} deprecation warnings - Fixed `information.gain` filter calculation. Before, `chi.squared` was calculated even though `information.gain` was requested due to a glitch in the filter naming (mlr-org#2816, @jokokojote) - Make `helpLearnerParam()`'s HTML parsing more robust (mlr-org#2843) - Add HTML5 support for help pages
mlr 2.19.0.9001 # mlr 2.19.0.9001 - Fixed `information.gain` filter calculation. Before, `chi.squared` was calculated even though `information.gain` was requested due to a glitch in the filter naming (mlr-org#2816, @jokokojote)
mlr 2.19.0
- Add filter `FSelectoRcpp::relief()`. This C++ based implementation of the RelieF filter algorithm is way faster than the Java based one from the {FSelector} package (mlr-org#2804)
- Fix S3 print method for `FilterWrapper` objects
- Make ibrier measure work with survival tasks (mlr-org#2789)
- Switch to testthat v3 (mlr-org#2796)
- Enable parallel tests (mlr-org#2796)
- Replace package PMCMR by PMCMRplus (mlr-org#2796)
- Remove CoxBoost learner due to CRAN removal
- Warning if `fix.factors.prediction = TRUE` causes the generation of NAs for new factor levels in prediction (@jakob-r, mlr-org#2794)
- Clear error message if prediction of wrapped learner has not the same length as `newdata` (@jakob-r, mlr-org#2794)
mlr 2.19.0-rc
- Add filter `FSelectoRcpp::relief()`. This C++ based implementation of the RelieF filter algorithm is way faster than the Java based one from the {FSelector} package (mlr-org#2804)
- Fix S3 print method for `FilterWrapper` objects
- Make ibrier measure work with survival tasks (mlr-org#2789)
- Switch to testthat v3 (mlr-org#2796)
- Enable parallel tests (mlr-org#2796)
- Replace package PMCMR by PMCMRplus (mlr-org#2796)
- Remove CoxBoost learner due to CRAN removal
- Warning if `fix.factors.prediction = TRUE` causes the generation of NAs for new factor levels in prediction (@jakob-r, mlr-org#2794)
- Clear error message if prediction of wrapped learner has not the same length as `newdata` (@jakob-r, mlr-org#2794)
mlr 2.19.0-rc
- Add filter `FSelectoRcpp::relief()`. This C++ based implementation of the RelieF filter algorithm is way faster than the Java based one from the {FSelector} package (mlr-org#2804)
- Fix S3 print method for `FilterWrapper` objects
- Make ibrier measure work with survival tasks (mlr-org#2789)
- Switch to testthat v3 (mlr-org#2796)
- Enable parallel tests (mlr-org#2796)
- Replace package PMCMR by PMCMRplus (mlr-org#2796)
- Remove CoxBoost learner due to CRAN removal
- Warning if `fix.factors.prediction = TRUE` causes the generation of NAs for new factor levels in prediction (@jakob-r, mlr-org#2794)
- Clear error message if prediction of wrapped learner has not the same length as `newdata` (@jakob-r, mlr-org#2794)
mlr 2.18.0.9003
- Add filter `FSelectoRcpp::relief()`. This C++ based implementation of the RelieF filter algorithm is way faster than the Java based one from the {FSelector} package (mlr-org#2804)
- Fix S3 print method for `FilterWrapper` objects
mlr 2.18.0.9002 - Switch to testthat v3 (mlr-org#2796) - Enable parallel tests (mlr-org#2796) - replace package PMCMR by PMCMRplus (mlr-org#2796) - Remove CoxBoost learner due to CRAN removal - Silence warnings in tests
mlr 2.18.0.9001 - Warning if `fix.factors.prediction = TRUE` causes the generation of NAs for new factor levels in prediction (@jakob-r, mlr-org#2794) - Clear error message if prediction of wrapped learner has not the same length as `newdata` (@jakob-r, mlr-org#2794)
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