In tkonopka/mlensemble: Ensembles of Machine Learning Models

Synopsis

Package mlensemble provides a framework for managing ensembles of machine learning models in R. Importantly, the framework does not train or evaluate individual models. It only provides an interface for putting existing models together into ensembles.

The framework is agnostic to the implementation details of individual models. This approach allows ensembles to have heterogeneous components, e.g. models trained on different training datasets or with different feature sets. At the same time, the framework allows for ensemble calibration. Calibration tunes how individual models contribute to integrated predictions. This offers a means to adjust ensembles to new datasets without the need to retrain the underlying models.