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renesasseddiebergmanCarolin Benjaminsmfeurerdependabot[bot]
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Version 1.3.4 (#857)
* Added reference to JMLR paper. * Typos in documentations. * Code more readable since all typings are imported at the beginning of the file. * Updated stale bot options. Co-authored-by: eddiebergman <[email protected]> Co-authored-by: Carolin Benjamins <[email protected]> Co-authored-by: Matthias Feurer <[email protected]> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
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.github/dependabot.yml

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version: 2
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updates:
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# This will check for updates to github actions every day
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# https://docs.github.com/en/[email protected]/code-security/dependabot/working-with-dependabot/keeping-your-actions-up-to-date-with-dependabot
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- package-ecosystem: "github-actions"
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directory: "/"
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.github/stale.yml

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- security
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- bug
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- dependency
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- documentation
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- enhancement
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- example
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staleLabel: wontfix
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staleLabel: stale
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# Comment to post when marking an issue as stale. Set to `false` to disable
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.github/workflows/citation.yml

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.github/workflows/dist.yml

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.github/workflows/docs.yml

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.github/workflows/pre-commit.yml

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README.md

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def train_random_forest(config):
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"""
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Trains a random forest on the given hyperparameters, defined by config, and returns the accuracy
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on the validation data.
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Input:
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config (Configuration): Configuration object derived from ConfigurationSpace.
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cost (float): Performance measure on the validation data.
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"""
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If you have found a bug, please report to [issues](https://github.com/automl/SMAC3/issues). Moreover, we are appreciating any kind of help.
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Find our guidlines for contributing to this package [here](https://github.com/automl/SMAC3/blob/master/.github/CONTRIBUTING.md).
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If you use SMAC in one of your research projects, please cite us:
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If you use SMAC in one of your research projects, please cite our [JMLR paper](https://jmlr.org/papers/v23/21-0888.html):
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```
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@misc{lindauer2021smac3,
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title={SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization},
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author={Marius Lindauer and Katharina Eggensperger and Matthias Feurer and André Biedenkapp and Difan Deng and Carolin Benjamins and Tim Ruhkopf and René Sass and Frank Hutter},
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year={2021},
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eprint={2109.09831},
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archivePrefix={arXiv},
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primaryClass={cs.LG}
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@article{JMLR:v23:21-0888,
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author = {Marius Lindauer and Katharina Eggensperger and Matthias Feurer and André Biedenkapp and Difan Deng and Carolin Benjamins and Tim Ruhkopf and René Sass and Frank Hutter},
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title = {SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization},
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journal = {Journal of Machine Learning Research},
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year = {2022},
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volume = {23},
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number = {54},
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pages = {1--9},
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url = {http://jmlr.org/papers/v23/21-0888.html}
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}
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```
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Copyright (C) 2016-2021 [AutoML Group](http://www.automl.org/).
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Copyright (C) 2016-2022 [AutoML Group](http://www.automl.org/).

changelog.md

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# 1.3.4
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* Added reference to JMLR paper.
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* Typos in documentations.
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* Code more readable since all typings are imported at the beginning of the file.
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* Updated stale bot options.
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# 1.3.3
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* Hotfix: Since multi-objective implementation depends on normalized costs, it now is ensured that the
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cached costs are updated everytime a new entry is added.

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