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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Machine Learning in R
- machine-learning
- data-science
- tuning
- cran
mlr3: Machine Learning in R - next generation
- machine-learning
- data-science
- classification
- regression
R interface for Apache Spark
Personal website
- r
- tidymodels
- tidyverse
- quarto