Loading deepchem/hyper/base_classes.py +1 −1 Original line number Diff line number Diff line Loading @@ -111,7 +111,7 @@ class HyperparamOpt(object): `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. nb_epoch: int, (default 5) nb_epoch: int, (default 10) Specifies the number of training epochs during each iteration of optimization. use_max: bool, optional If True, return the model with the highest score. Else return Loading deepchem/hyper/gaussian_process.py +1 −1 Original line number Diff line number Diff line Loading @@ -161,7 +161,7 @@ class GaussianProcessHyperparamOpt(HyperparamOpt): `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. nb_epoch: int, (default 5) nb_epoch: int, (default 10) Specifies the number of training epochs during each iteration of optimization. Not used by all model types. use_max: bool, (default True) Loading deepchem/hyper/grid_search.py +1 −1 Original line number Diff line number Diff line Loading @@ -92,7 +92,7 @@ class GridHyperparamOpt(HyperparamOpt): `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. nb_epoch: int, (default 5) nb_epoch: int, (default 10) Specifies the number of training epochs during each iteration of optimization. Not used by all model types. use_max: bool, optional Loading Loading
deepchem/hyper/base_classes.py +1 −1 Original line number Diff line number Diff line Loading @@ -111,7 +111,7 @@ class HyperparamOpt(object): `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. nb_epoch: int, (default 5) nb_epoch: int, (default 10) Specifies the number of training epochs during each iteration of optimization. use_max: bool, optional If True, return the model with the highest score. Else return Loading
deepchem/hyper/gaussian_process.py +1 −1 Original line number Diff line number Diff line Loading @@ -161,7 +161,7 @@ class GaussianProcessHyperparamOpt(HyperparamOpt): `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. nb_epoch: int, (default 5) nb_epoch: int, (default 10) Specifies the number of training epochs during each iteration of optimization. Not used by all model types. use_max: bool, (default True) Loading
deepchem/hyper/grid_search.py +1 −1 Original line number Diff line number Diff line Loading @@ -92,7 +92,7 @@ class GridHyperparamOpt(HyperparamOpt): `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. nb_epoch: int, (default 5) nb_epoch: int, (default 10) Specifies the number of training epochs during each iteration of optimization. Not used by all model types. use_max: bool, optional Loading
