SMAC3
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization (by automl)
optuna-examples
Examples for https://github.com/optuna/optuna (by optuna)
SMAC3 | optuna-examples | |
---|---|---|
2 | 2 | |
1,009 | 599 | |
2.4% | 4.0% | |
3.2 | 8.7 | |
11 days ago | 5 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SMAC3
Posts with mentions or reviews of SMAC3.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-12.
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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
optuna-examples
Posts with mentions or reviews of optuna-examples.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-08-12.
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[D]How to optimize an ANN?
Check out the examples for Optuna, a popular hyper parameter tuning package. It has examples for most popular ML frameworks including Xgboost, so you can see how it compares to an ANN framework like Keras or PyTorch.
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Data Scientists are dying out
That's still regular ML because you are in charge of the features. Optuna might make your life easier though: https://github.com/optuna/optuna-examples/blob/main/xgboost/xgboost_simple.py
What are some alternatives?
When comparing SMAC3 and optuna-examples you can also consider the following projects:
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
tqdm - :zap: A Fast, Extensible Progress Bar for Python and CLI
optuna - A hyperparameter optimization framework
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.