Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised. Tuning examples include optimizing regularization or kernel parameters.
From an optimization point of view, the tuning problem can be considered as follows: the objective function is non-convex, non-differentiable and typically expensive to evaluate.
This package provides several distinct approaches to solve such problems including some helpful facilities such as cross-validation and a plethora of score functions.
The Optunity library is implemented in Python and allows straightforward integration in other machine learning environments, including R and MATLAB.
If you have any comments, suggestions you can get in touch with us at gitter:
To get started with Optunity on Linux, issue the following commands:
git clone https://github.com/claesenm/optunity.git echo "export PYTHONPATH=$PYTHONPATH:$(pwd)/optunity" >> ~/.bashrc
Afterwards, importing optunity should work in Python:
#!/usr/bin/env python import optunity
Optunity is developed at the STADIUS lab of the dept. of electrical engineering at KU Leuven (ESAT). Optunity is free software, using a BSD license.
For more information, please refer to the following pages: http://www.optunity.net
Contributors
The main contributors to Optunity are:
Marc Claesen: framework design & implementation, communication infrastructure, MATLAB wrapper and all solvers.
Jaak Simm: R wrapper.
1 maintainer
Metadata
1 maintainer
Release files for Optunity 1.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| Optunity-1.1.1.tar.gz | 4.6 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Optunity-1.1.1-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 4.6 MB
Release files / Optunity-1.1.1.tar.gz
| Download URL | Optunity-1.1.1.tar.gz |
|---|---|
| Size | 4.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a83618dd37e014c5993e8877749e0ee17864d24783f19f5ebdeedb5525c0a65b
|
|
BLAKE2b-256 checksum How to use checksums |
324dd49876a49e105b56755eb5ba06a4848ee8010f7ff9e0f11a13aefed12063
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / Optunity-1.1.1-py2-none-any.whl
| Download URL | Optunity-1.1.1-py2-none-any.whl |
|---|---|
| Size | 73.2 kB |
| Tags | Python 2 |
|
SHA-256 checksum How to use checksums |
28c6a9104872c580f46648c7fd1f4a2b39e10593c1eb31f61f6da1acd275f07c
|
|
BLAKE2b-256 checksum How to use checksums |
5b81f19ec2e937175d393cd4b05ac5c556f62e35052ba0c55789fd23a746274a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for Optunity 1.1.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
