SMAC3
syne-tune
| SMAC3 | syne-tune | |
|---|---|---|
| 2 | 1 | |
| 1,009 | 363 | |
| 2.3% | 0.6% | |
| 3.2 | 8.1 | |
| 10 days ago | 6 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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SMAC3
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[D]How to optimize an ANN?
You can use Optuna, SMAC or hyperopt
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Finding the optimal parameter
Apart from the aforementioned comments noting that this is an optimization problem, ready-to-use python libraries for this kind of problem (accounting for evaluation time) include http://hyperopt.github.io/hyperopt/, https://github.com/automl/SMAC3, or https://www.ray.io/ray-tune
syne-tune
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Amazon AI Researchers Open-Source ‘Syne Tune’: A Novel Python Library For Distributed HPO With An Emphasis On Enabling Reproducible Machine Learning Research
Continue reading | Checkout the paper, github
What are some alternatives?
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
auto-sklearn - Automated Machine Learning with scikit-learn
optuna - A hyperparameter optimization framework
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
optuna-examples - Examples for https://github.com/optuna/optuna
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
OCTIS - OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)