Saving or logging an entire experiment in PyCaret is as simple as writing save_experiment. The function saves the entire environment including transformation pipeline, models created and all the intermediary outputs as a transferable binary pickle file for later use.
# Importing dataset from pycaret.datasets import get_data boston = get_data('boston') # Importing module and initializing setup from pycaret.regression import * reg1 = setup(data = boston, target = 'medv') # compare models compare_models() # create a model xgboost = create_model('xgboost') # blend models blend_models() #saving an experiment save_experiment('experiment_07032020')
Loading saved experiment
# Loading saved experiment experiment_saved = load_experiment('experiment_07032020')
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