Artifacts using MlrMBO (2)

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Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners ...
Last Release on May 1, 2022
Tuning random forest with one line. The package is mainly based on the packages 'ranger' and 'mlrMBO'.
Last Release on May 2, 2022
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