Hyperparameter optimization: Difference between revisions

Revision as of 04:52, 17 December 2017

Revision as of 05:02, 25 December 2017

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===Grid search===

* [[LIBSVM]] comes with scripts for performing grid search.

* [[scikit-learn]] is a Python package which includes [http://scikit-learn.sourceforge.net/modules/grid_search.html grid] search.

===Bayesian===

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===Random search===

* [https://github.com/hyperopt/hyperopt hyperopt] and [https://github.com/hyperopt/hyperopt-sklearn hyperopt-sklearn] are Python packages which include random search.

* [[scikit-learn]] is a Python package which includes [http://scikit-learn.org/stable/modules/generated/sklearn.grid_search.RandomizedSearchCV.html random] search.

===Gradient based===

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===Other===

* [https://github.com/hyperopt/hyperopt hyperopt] and [https://github.com/hyperopt/hyperopt-sklearn hyperopt-sklearn] are Python packages forwhich include [[kernel density estimation|Tree of Parzen Estimators]] based distributed hyperparameter optimization.

* [https://github.com/CMA-ES/pycma pycma] is a Python implementation of [[CMA-ES|Covariance Matrix Adaptation Evolution Strategy]].

* [http://sumo.intec.ugent.be SUMO-Toolbox]<ref name="gorissen">{{cite journal