meta_models ¶
get_tabpfn_outer_ensemble ¶
This will create a model very similar to our standard TabPFN estimators,
but it uses multiple model weights to generate predictions.
Thus the configs.TabPFNModelPathsConfig can contain multiple paths which are all used.
A product of the preprocessor_trasnforms and paths is created to yield interesting ensemble members.
This only supports multiclass for now. If you want to add regression, you probably want to add the y_transforms to the relevant_config_product. :param config: TabPFNConfig :param kwargs: kwargs are passed to get_single_tabpfn, e.g. device :return: A TabPFNEnsemble, which is a soft voting classifier that mixes multiple standard TabPFN estimators.