A Python port of the R Cubist library.
Project description
Cubist
A Python package for fitting Ross Quinlan's Cubist v2.07 regression model. Inspired by and based on the R wrapper for Cubist. Designed after and inherits from the scikit-learn framework.
Background
Cubist is a novel regression algorithm develped by Ross Quinlan...
Use
>>> from cubist import Cubist
>>> model = Cubist()
>>> model.fit(X, y)
>>> model.predict(X)
Benchmarks
From literature, there examples of Cubist outperforming RandomForest and other boosted models, to demonstrate this, the following benchmarks are provided to compare models. The scripts that achieved these results are provided in the benchmarks folder.
Building
python -m build --sdist --wheel .
Installing from Source
pip install --upgrade .
Interesting Links:
- https://www.linkedin.com/pulse/machine-learning-example-r-using-cubist-kirk-mettler http://rulequest.com/cubist-info.html
Literature
Release history Release notifications | RSS feed
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