Benchmarks¶

River benchmarks track the timing performance of models across git history using airspeed velocity (asv).

View benchmark results

The benchmarks cover three tracks:

• Binary classification — Logistic regression, AMF, ALMA on Bananas, Phishing
• Multiclass classification — Naive Bayes, Hoeffding Trees, Random Forests, ensembles, KNN on ImageSegments
• Regression — Linear models, trees, forests, ensembles, MLP on ChickWeights, TrumpApproval

Each benchmark runs full progressive validation (evaluate.iter_progressive_val_score) and measures wall-clock time. See the benchmarks README for instructions on running benchmarks locally.