In case if we can avoid certain stages used during training while predicting we need to propagate
some changes to the model (eg. unscale weights or remove intercept). Also useful for extending summary
blocks (eg. during evaluation/cross-validation).
This interface defines the logic of model transformation.
Linear Supertypes
Model[T], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
In case if we can avoid certain stages used during training while predicting we need to propagate some changes to the model (eg. unscale weights or remove intercept). Also useful for extending summary blocks (eg. during evaluation/cross-validation).
This interface defines the logic of model transformation.