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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.).

Reporter classes for the jasmine test framework. Includes JUnitXmlReporter for generating junit xml output for running in CI environments like Jenkins.