pyfru documentation

Fru-arrow

R version | Pyfru docs

Fru-arrow is a highly performant implementation of the Random Forest model. It uses Arrow PyCapsule underneath, making integration with any library that supports it - polars, pandas, pyarrow straightforward. Moreover, it features permutation importance with a novel, highly optimized algorithm. It can be used for both classification and regression, as well as out-of-bag predictions.

Fru is typically anywhere from a few times to several thousand times faster than scikit-learn’s Random Forest implementation. The performance gap widens as the number of threads increases.

The plot below illustrates this difference.