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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Glue strings to data in R. Small, fast, dependency free interpreted string literals.
- r
- strings
- string-interpolation
Tidy anomaly detection
- detect-anomalies
- decomposition
- iqr
- time-series
Accelerated similarity searching of small molecules (bioconductor package)