Show HN: Crforest – Competing-risks RSF in Python, 6× faster than R's rfSRC

Category: library

Tags: survival-analysis, competing-risks, random-forest, python, machine-learning

Score: 7.3/10 (Innovation: 8, Technical: 8, Documentation: 7, Utility: 6)

crforest is a Python implementation of competing-risks random survival forests that is 4.5–6× faster than the leading R package randomForestSRC and scales to millions of samples. It addresses a long-standing gap by providing a native, fast, scikit-learn-compatible tool for survival analysis with multiple competing events, eliminating the need for Python-to-R workarounds.

Target audience: data scientists, biostatisticians, clinical researchers

Repository: https://github.com/sunnyadn/crforest · Python · Apache-2.0 · 1 stars

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