def METHOD_NAME(cls, data) -> Type['PredictorNode']:
    """Return the subtype."""
    from .expression_predictor import ExpressionPredictor
    from .molecular_structure_featurizer import MolecularStructureFeaturizer
    from .ingredients_to_formulation_predictor import IngredientsToFormulationPredictor
    from .label_fractions_predictor import LabelFractionsPredictor
    from .simple_mixture_predictor import SimpleMixturePredictor
    from .ingredient_fractions_predictor import IngredientFractionsPredictor
    from .auto_ml_predictor import AutoMLPredictor
    from .mean_property_predictor import MeanPropertyPredictor
    from .chemical_formula_featurizer import ChemicalFormulaFeaturizer
    type_dict = {
        "AnalyticExpression": ExpressionPredictor,
        "MoleculeFeaturizer": MolecularStructureFeaturizer,
        "IngredientsToSimpleMixture": IngredientsToFormulationPredictor,
        "MeanProperty": MeanPropertyPredictor,
        "LabelFractions": LabelFractionsPredictor,
        "SimpleMixture": SimpleMixturePredictor,
        "IngredientFractions": IngredientFractionsPredictor,
        "ChemicalFormulaFeaturizer": ChemicalFormulaFeaturizer,
        "AutoML": AutoMLPredictor,
    }
    typ = type_dict.get(data['type'])
    if typ is not None:
        return typ
    else:
        raise ValueError(
            '{} is not a valid predictor node type. '
            'Must be in {}.'.format(data['type'], type_dict.keys())
        )