Project details for Optunity

Screenshot Optunity 1.1.1

by claesenm - September 30, 2015, 07:06:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

view ( today), download ( today ), 0 subscriptions


Optunity provides a variety of solvers for hyperparameter tuning problems. The software offers a diverse set of solvers to optimize hyperparameters.

The first major release of Optunity (stable). For documentation, please refer to Optunity is compatible with Python 2.7 and above.

The following features are available:

Wide variety of solvers:

  • particle swarm optimization
  • Nelder-Mead
  • grid search
  • random search
  • Sobol sequences
  • CMA-ES (requires DEAP and NumPy)
  • TPE (requires Hyperopt and NumPy)

Generic cross-validation functionality:

  • support for strata and clusters
  • folds are reusable for multiple learning algorithm/solver combinations

Various quality metrics for models (score/loss functions).

Univariate domain constraints on hyperparameters.

Support for parallel objective function evaluations.

Support for structured search spaces.

This release provides Optunity functionality in the following environments: * MATLAB R Octave

Changes to previous version:

This minor release has the same feature set as Optunity 1.1.0, but incorporates several bug fixes, mostly related to the specification of structured search spaces.

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Agnostic
Data Formats: Agnostic
Tags: Optimization, Hyperparameter Tuning
Archive: download here


No one has posted any comments yet. Perhaps you'd like to be the first?

Leave a comment

You must be logged in to post comments.