Gradient-boosting-machine Libraries

2 Components & Libraries

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Gradient-boosting-machine Libraries

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.).

The algorithms studied are in various commonly used open source implementations like In summary, we are focusing on which algos/implementations can be used to train relatively accurate binary classif…

interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Examples of techniques for training interpretable machine learning (ML) models, explaining ML models, and debugging ML models for accuracy, discrimination, and security. The notebooks highlight techn…

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pytorch

python