cubist 0.0.7

A Python port of the R Cubist library.

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

• https://sci2s.ugr.es/keel/pdf/algorithm/congreso/1992-Quinlan-AI.pdf
• http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.34.6358&rep=rep1&type=pdf