StackingNone

"StackingNone" typically refers to a setting in machine learning models where multiple predictive algorithms are combined but without using a stacking technique. Stacking usually involves training a new model to fuse the outputs of several models for better accuracy. When "StackingNone" is selected, it means the models are used separately or their outputs are combined through simple methods like averaging, rather than through a learned, layered approach. This setting is useful when we prefer straightforward combination methods over more complex stacking strategies for ensemble modeling.