AI, Python, Cognitive Neuroscience

Evolutionary Powell's method is a discrete optimization algorithm I've found useful for hyperparameter tuning.

It makes weaker assumptions than Bayesian methods (and so is more robust), but stronger than random exploration (and so has better performance). It fills in the gap between then a bit.

Here's the full post on how Evolutionary Powell's method works:

We develop it as part of End-to-End Machine Learning Course 314:

The open source Ponderosa optimization package where it lives:

The line-by-line code walkthrough:

❇️ @AI_Python_EN

www.tg-me.com/de/AI Python Cognitive Neuroscience/com.ai_python_en/2166

1.4K viewsFarzad, Dec 13, 2019 at 18:07

Evolutionary Powell's method is a discrete optimization algorithm I've found useful for hyperparameter tuning.

It makes weaker assumptions than Bayesian methods (and so is more robust), but stronger than random exploration (and so has better performance). It fills in the gap between then a bit.

Here's the full post on how Evolutionary Powell's method works:

We develop it as part of End-to-End Machine Learning Course 314:

The open source Ponderosa optimization package where it lives:

The line-by-line code walkthrough:

❇️ @AI_Python_EN

BY AI, Python, Cognitive Neuroscience