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release: 1.4.0 (#1449)
* refactor: rename warn_deprecated * release: 1.4.0 * ... * ... * ... * ... * ... * ... * ... * ... * ... * ...
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.Rbuildignore

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^.cursor$
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^local_attic$
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^tests/testthat/_object_snapshots$
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^.claude$

DESCRIPTION

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Package: mlr3
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Title: Machine Learning in R - Next Generation
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Version: 1.3.0.9000
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Version: 1.4.0
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Authors@R:
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c(
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person("Michel", "Lang", , "michellang@gmail.com", role = "aut",

NEWS.md

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# mlr3 (development version)
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# mlr3 1.4.0
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* feat: Add `$native_model` active binding to `Learner` to access the model from the upstream package.
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* feat: Learner store the condition of warnings and errors in the `log` field.
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* feat: No supervised tasks with missing target values are allowed anymore.
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* refactor: Validate the input of fields.
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* fix: Assert list input in `assert_learners`, `assert_tasks`, `assert_measures` and `assert_resamplings`.
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* fix: `convert_task` converts the internal validation task now.
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* fix: disable printing of class ratios for large tasks.
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* fix: Make quantiles resettable.
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# mlr3 1.3.0
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R/as_task_classif.R

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}
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if (anyMissing(x[[target]])) {
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error_input("Target column '%s' must not contain missing values", target)
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messagef("Target column '%s' contains missing values. This will be an error in the future.", target)
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# error_input("Target column '%s' must not contain missing values", target)
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}
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y = x[[target]]

R/as_task_regr.R

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}
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if (anyMissing(x[[target]])) {
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error_input("Target column '%s' must not contain missing values", target)
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messagef("Target column '%s' contains missing values. This will be an error in the future.", target)
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# error_input("Target column '%s' must not contain missing values", target)
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}
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TaskRegr$new(id = id, backend = x, target = target, label = label)

R/mlr_reflections.R

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#' @format [environment].
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#' @description
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#' Environment which stores various information to allow objects to examine and introspect their structure and properties
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#' (c.f. [Reflections](https://www.wikiwand.com/en/Reflection_(computer_programming))).
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#' (c.f. [Reflections](https://en.wikipedia.org/wiki/Reflective_programming)).
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#'
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#' This environment be modified by third-party packages, e.g. by adding information about new task types
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#' or by extending the set of allowed feature types.

man/mlr_reflections.Rd

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tests/testthat/_object_snapshots/snapshot.R

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task_classif = tsk("pima") # mlr3 1.2.0
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task_classif = tsk("pima") # mlr3 1.4.0
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saveRDS(task_classif, "tests/testthat/_object_snapshots/task_classif.rds")
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task_regr = tsk("mtcars") # mlr3 1.2.0
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task_regr = tsk("mtcars") # mlr3 1.4.0
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saveRDS(task_regr, "tests/testthat/_object_snapshots/task_regr.rds")
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learner_classif = lrn("classif.rpart") # mlr3 1.0.0
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resampling$instantiate(task_classif)
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saveRDS(resampling, "tests/testthat/_object_snapshots/resampling.rds")
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rr = resample(task_classif, learner_classif, resampling) # mlr3 1.2.0
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rr = resample(task_classif, learner_classif, resampling) # mlr3 1.4.0
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saveRDS(rr, "tests/testthat/_object_snapshots/rr.rds")
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design = benchmark_grid(
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resamplings = list(resampling)
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)
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bmr = benchmark(design) # mlr3 1.2.0
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bmr = benchmark(design) # mlr3 1.4.0
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saveRDS(bmr, "tests/testthat/_object_snapshots/bmr.rds")
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measure = msr("classif.ce") # mlr3 1.0.0

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