The :mod:`hyperactive.opt` module contains optimization algorithms for hyperparameter tuning.
All optimizers inherit from :class:`~hyperactive.base.BaseOptimizer` and share the same interface:
the solve() method to run optimization, and configuration via the experiment and search_space parameters.
Hyperactive provides optimizers from four backends:
| Backend | Description |
|---|---|
| :doc:`gfo` | Native gradient-free optimization algorithms (21 optimizers) |
| :doc:`optuna` | Interface to Optuna's samplers (8 optimizers) |
| :doc:`scipy` | Scipy.optimize algorithms for continuous spaces (7 optimizers) |
| :doc:`sklearn` | sklearn-compatible search interfaces (2 optimizers) |
.. toctree::
:maxdepth: 2
gfo
optuna
scipy
sklearn