robinthibaut/skbel
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
This tool helps scientists and researchers apply the Bayesian Evidential Learning (BEL) framework to their data analysis. You input your observational data and an existing simulation model, and it helps you combine them to get better predictions and understand uncertainties. Geoscientists, hydrologists, and environmental modelers who need to integrate diverse data sources would find this particularly useful.
No commits in the last 6 months. Available on PyPI.
Use this if you are a researcher in Earth Sciences or a related field needing to calibrate complex simulation models using real-world observations and quantify the uncertainty in your predictions.
Not ideal if you are looking for a general-purpose machine learning library without a specific focus on Bayesian Evidential Learning or if you don't have a pre-existing simulation model.
Stars
26
Forks
5
Language
Python
License
BSD-3-Clause
Category
Last pushed
Jul 09, 2024
Commits (30d)
0
Dependencies
8
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