Loading examples/qm7/qm7_sklearn.py +6 −3 Original line number Diff line number Diff line Loading @@ -17,12 +17,15 @@ tasks, datasets, transformers = dc.molnet.load_qm7( train, valid, test = datasets regression_metric = dc.metrics.Metric(dc.metrics.mean_absolute_error, mode="regression") regression_metric = dc.metrics.Metric( dc.metrics.mean_absolute_error, mode="regression") def model_builder(model_dir): sklearn_model = KernelRidge( kernel="rbf", alpha=5e-4, gamma=0.008) sklearn_model = KernelRidge(kernel="rbf", alpha=5e-4, gamma=0.008) return dc.models.SklearnModel(sklearn_model, model_dir) model = dc.models.SingletaskToMultitask(tasks, model_builder) # Fit trained model Loading Loading
examples/qm7/qm7_sklearn.py +6 −3 Original line number Diff line number Diff line Loading @@ -17,12 +17,15 @@ tasks, datasets, transformers = dc.molnet.load_qm7( train, valid, test = datasets regression_metric = dc.metrics.Metric(dc.metrics.mean_absolute_error, mode="regression") regression_metric = dc.metrics.Metric( dc.metrics.mean_absolute_error, mode="regression") def model_builder(model_dir): sklearn_model = KernelRidge( kernel="rbf", alpha=5e-4, gamma=0.008) sklearn_model = KernelRidge(kernel="rbf", alpha=5e-4, gamma=0.008) return dc.models.SklearnModel(sklearn_model, model_dir) model = dc.models.SingletaskToMultitask(tasks, model_builder) # Fit trained model Loading
