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Tags: Benchmarking
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1–13 of 13 · Most stars

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Measure and explain performance: web pages, Electron apps, Bun/Node, any process. Agent-native CLI + MCP.