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.).
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:christmas_tree:Visualization and annotation of phylogenetic trees
- r
- visualization
- phylogenetic-trees
- annotations
Random forests for R for large data sets, optimized with parallel tree-growing and disk-based memory