Loading deepchem/models/sklearn_models/__init__.py +19 −4 Original line number Diff line number Diff line Loading @@ -16,10 +16,10 @@ from deepchem.models import Model from deepchem.utils.save import load_from_disk from deepchem.utils.save import save_to_disk NON_WEIGHTED_MODELS = { NON_WEIGHTED_MODELS = [ LogisticRegression, PLSRegression, GaussianProcessRegressor, ElasticNetCV, LassoCV, BayesianRidge } ] class SklearnModel(Model): Loading @@ -27,8 +27,23 @@ class SklearnModel(Model): Abstract base class for different ML models. """ def __init__(self, **kwargs): super(SklearnModel, self).__init__(**kwargs) def __init__(self, model_instance=None, model_dir=None, verbose=True, **kwargs): """ Parameters ---------- model_instance: sklearn model model_dir: str verbose: bool kwargs: dict kwargs['use_weights'] is a bool which determines if we pass weights into self.model_instance.fit() """ super(SklearnModel, self).__init__(model_instance, model_dir, verbose, **kwargs) if 'use_weights' in kwargs: self.use_weights = kwargs['use_weights'] else: Loading Loading
deepchem/models/sklearn_models/__init__.py +19 −4 Original line number Diff line number Diff line Loading @@ -16,10 +16,10 @@ from deepchem.models import Model from deepchem.utils.save import load_from_disk from deepchem.utils.save import save_to_disk NON_WEIGHTED_MODELS = { NON_WEIGHTED_MODELS = [ LogisticRegression, PLSRegression, GaussianProcessRegressor, ElasticNetCV, LassoCV, BayesianRidge } ] class SklearnModel(Model): Loading @@ -27,8 +27,23 @@ class SklearnModel(Model): Abstract base class for different ML models. """ def __init__(self, **kwargs): super(SklearnModel, self).__init__(**kwargs) def __init__(self, model_instance=None, model_dir=None, verbose=True, **kwargs): """ Parameters ---------- model_instance: sklearn model model_dir: str verbose: bool kwargs: dict kwargs['use_weights'] is a bool which determines if we pass weights into self.model_instance.fit() """ super(SklearnModel, self).__init__(model_instance, model_dir, verbose, **kwargs) if 'use_weights' in kwargs: self.use_weights = kwargs['use_weights'] else: Loading
