The following new namespaces appear in the run metadata: Name To copy it, navigate to the project settings → Properties.
Pip install xgboost full#
To log to your own workspace, pass the full name of your Neptune project: workspace-name/project-name. Projects in the common workspace are public and can be used for testing.Once you register, you should leave the token out of your script and instead save it as an environment variable. The api_token argument is included to enable anonymous logging.fit ( X_train, y_train, early_stopping_rounds = 30, eval_metric =, eval_set =, callbacks =, ) # Stop run run. XGBRegressor ( ** model_params ) # Fit the model and log metadata to the run in Neptune reg. DMatrix ( X_test, label = y_test ) # Define parameters model_params = reg = xgb. DMatrix ( X_train, label = y_train ) dval = xgb. ANONYMOUS_API_TOKEN, # (1) project = "common/xgboost-integration", # (2) name = "xgb-cv", # optional tags =, # optional ) # Create Neptune callback neptune_callback = NeptuneCallback ( run = run, log_tree = ) # Prepare data X, y = load_california_housing ( return_X_y = True ) X_train, X_test, y_train, y_test = train_test_split ( X, y, test_size = 0.2, random_state = 123 ) dtrain = xgb. Import neptune.new as neptune import xgboost as xgb from import NeptuneCallback from sklearn.datasets import load_california_housing from sklearn.model_selection import train_test_split # Create run run = neptune. Installing the Neptune–XGBoost integration
Logging in to Neptune with a third-party account Querying metadata from the model registryĬombining several metadata types in one dashboard
0 kommentar(er)
