Hyperparameter optimization: Difference between revisions

Revision as of 21:59, 9 December 2017

Revision as of 04:38, 17 December 2017

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===Other===

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

* [https://jaberg.github.com/hyperopt/ Hyperopt] is a distributed hyperparameter optimization library in Python.

* [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

| title = A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design

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}}</ref> is a [[MATLAB]] toolbox for [[surrogate model]]ing supporting a wide collection of hyperparameter optimization algorithm for many model types.

* [https://github.com/coin-or/rbfopt rbfopt] is a Python package that uses a [[radial basis function]] model<ref name=abs1705.08520/>

* [https://github.com/callowbird/Harmonica Harmonica] is a Python 3 package for spectral hyperparameter optimization.<ref name=abs1706.00764/>

===Multiple===