Loading examples/sider/sider_rf.py +5 −2 Original line number Diff line number Diff line Loading @@ -15,13 +15,16 @@ from sklearn.ensemble import RandomForestClassifier sider_tasks, datasets, transformers = dc.molnet.load_sider() train_dataset, valid_dataset, test_dataset = datasets metric = dc.metrics.Metric(dc.metrics.roc_auc_score, np.mean, mode="classification") metric = dc.metrics.Metric( dc.metrics.roc_auc_score, np.mean, mode="classification") def model_builder(model_dir): sklearn_model = RandomForestClassifier( class_weight="balanced", n_estimators=100) return dc.models.SklearnModel(sklearn_model, model_dir) model = dc.models.SingletaskToMultitask(sider_tasks, model_builder) # Fit trained model Loading Loading
examples/sider/sider_rf.py +5 −2 Original line number Diff line number Diff line Loading @@ -15,13 +15,16 @@ from sklearn.ensemble import RandomForestClassifier sider_tasks, datasets, transformers = dc.molnet.load_sider() train_dataset, valid_dataset, test_dataset = datasets metric = dc.metrics.Metric(dc.metrics.roc_auc_score, np.mean, mode="classification") metric = dc.metrics.Metric( dc.metrics.roc_auc_score, np.mean, mode="classification") def model_builder(model_dir): sklearn_model = RandomForestClassifier( class_weight="balanced", n_estimators=100) return dc.models.SklearnModel(sklearn_model, model_dir) model = dc.models.SingletaskToMultitask(sider_tasks, model_builder) # Fit trained model Loading
