blei-lab/treeffuser
Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion models.
Treeffuser helps analysts, data scientists, and researchers make detailed probabilistic predictions from tabular data. It takes your existing dataset, with input features and a target variable, and produces a full distribution of possible outcomes for new inputs. This allows you to understand the range and likelihood of different results, not just a single best guess.
Available on PyPI.
Use this if you need to understand the full spectrum of possible outcomes for a prediction, especially when the relationship between your inputs and outputs is complex, like having multiple possible results or varying uncertainty.
Not ideal if you only need a single point estimate for your prediction and are not interested in the uncertainty or the full probability distribution of the outcomes.
Stars
55
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9
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 16, 2026
Commits (30d)
0
Dependencies
9
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