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# Goal
As a machine learning developer, I want to use genetic algorithms and bayesian optimization, so that I can determine the best parameters for any indicator.
# Inspiration
For cryptocurrency …
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# Rational:
Machine learning models usually apply meta-parameter optimization to find the learning parameters that lead to the better learning and better cross-validation. So to here, to get a bio…
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Hi all,
I am working on optimizing a black box function. The problem has 52 variables.
PyNOMAD on running for around 2.5 hours (BB function evaluation is costly) is giving inferior answers as comp…
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Such as this https://uhra.herts.ac.uk/handle/2299/18193 applied to ants, using S-Net.
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Here we collect a series of algorithms that have been repurposed for generative art
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Is it possible to do neural network topology optimization with Pybrain?
For example network pruning such as optimal brain damage or finding the optimal topology with genetic algorithms?
If this is no…
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The content is put to https://github.com/husky-team/husky/wiki/TODO:-Format-of-Machine-Learning-API
I have thought of several choices, but I don't have a clue of which one is absolutely better. Cur…
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I see you are writing Python code for gradient descent optimization on GitHub. A general problem for gradient descent, particularly for more complex equations, is the choice of initial parameters to s…
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*Issue migrated from trac ticket # 2463*
**milestone:** HeuristicLab 4.x Backlog | **component:** Optimization.Views | **priority:** medium
#### 2015-08-13 19:34:34: @abeham created the issue
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Any collaborator is most welcome to contribute additional advanced methods to this repository.