hgboost

hgboost_save_load.py

# Save model
status = hgb.save(filepath='hgboost_model.pkl', overwrite=True)
# [pypickle] Pickle file saved: [hgboost_model.pkl]
# [hgboost] >Saving.. True

# Load model
From hgboost import hgboost                      # Import library when using a fresh start
hgb = hgboost()                                  # Initialize hgboost
results = hgb.load(filepath='hgboost_model.pkl') # Load the pickle file with model parameters and trained model.
# [pypickle] Pickle file loaded: [hgboost_model.pkl]
# [hgboost] >Loading succesful!

# Make predictions again
y_pred, y_proba = hgb.predict(X)