NiklasPfister/adaXT
adaXT: tree-based machine learning in Python
This project helps machine learning researchers build and experiment with custom tree-based models, such as decision trees and random forests. You input your dataset and define how the trees should learn and make predictions. It outputs fitted models that can classify data, predict continuous values, estimate uncertainty (quantiles), or calculate derivatives, offering a flexible environment for developing new algorithms.
No commits in the last 6 months. Available on PyPI.
Use this if you are a researcher developing new tree-based machine learning algorithms and need a flexible, adaptable framework for prototyping ideas beyond standard implementations.
Not ideal if your primary concern is achieving the absolute fastest prediction speeds with existing, off-the-shelf tree algorithms, as more specialized packages might offer greater optimization.
Stars
11
Forks
2
Language
Python
License
BSD-3-Clause
Category
Last pushed
May 28, 2025
Commits (30d)
0
Dependencies
3
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