Uses of Interface

Packages that use SparseTrainer
Provides implementations of decision trees for classification problems.
Provides an implementation of LIME (Locally Interpretable Model Explanations).
Provides common functionality for building decision trees, irrespective of the predicted Output.
Provides skeletal implementations of Regressor Trainer that can wrap a single dimension trainer/model and produce one prediction per dimension independently.
Provides an implementation of decision trees for regression problems.
Provides implementations of sparse linear regression using various forms of regularisation penalty.