leveraging aisara algorithm for effective hyperparameter tuning
Project description
aisaratuners is a hyperparameter tuning library that can be used with different machine learning and deep learning python packages including scikit-learn, PyTorch and keras. aisaratuners leverages AiSara algorithm, Latin hypercube sampling, and the concept of search space reduction for fast reach of the optimum hyperparameters combination.
Change Log
1.2 (19/11/2020)
- First Release
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
aisaratuners-1.2.tar.gz
(9.7 kB
view hashes)
Built Distribution
aisaratuners-1.2-py3-none-any.whl
(10.4 kB
view hashes)
Close
Hashes for aisaratuners-1.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8c3f180137a1351e4bfff1ce3cf5fbeabc7d63453ae05889ce560c30fdf090b0 |
|
MD5 | a3aba2f5bbf10835ee77c6ba88a64ae9 |
|
BLAKE2b-256 | df1e39527560f1ef740a9bac90599dcb0a349576e1498ee3e3ff4ae8ae0eb040 |