AI BriefingRust-based Random Forest Released
Key point
fru, a Rust-based Random Forest implementation, has been released with Python and R bindings, highlighting high performance.
Details
fru is a Random Forest library implemented in Rust, offering bindings for Python and R.
The development team presented the following performance results compared to major implementations:
- In Python, it is several times faster than scikit-learn, with improvements of hundreds of times in some use cases
- In R, it is generally tens of percent faster than ranger, with improvements of several times depending on conditions
- Variable importance calculation performance is also improved via a custom-implemented permutation importance
The Python binding is designed to interoperate with compatible libraries such as pandas, Polars, and PyArrow by using Arrow PyCapsule. The related research was published in the Software X journal.
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