SuperLearner
An R package for automatic optimal predictor ensembling via cross-validation with dozens of machine learning algorithms.
What is SuperLearner?
SuperLearner is an R package that implements a prediction model ensembling method, automatically combining multiple machine learning algorithms through cross-validation to create optimal predictive models. It solves the problem of model selection by letting data determine the best combination of algorithms rather than relying on a single approach.
Data scientists, statisticians, and researchers working on predictive modeling tasks in R who need robust, automated ensemble methods.
Developers choose SuperLearner for its one-line automatic ensembling, extensive algorithm library, and flexibility in customizing algorithms, loss functions, and metrics, making it a comprehensive tool for building high-performance predictive models.
Overview
Current version of the SuperLearner R package
Use Cases
Best For
- Building automated ensemble models for predictive analytics
- Comparing multiple machine learning algorithms on a dataset
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