pycaret is a very compact tool to compare models that I wanted to use for model selection. Unfortunately, the method compare_models does not show the typical output table that you see everywhere. I am using pycaret in PyCharm and not Jupyter Notebook which seems to be the typical approach. I do get the best model as a return value, but am really aiming for the overview table. It also doesn't seem to make a difference whether the parameter silent
is set to True
or False
appart from being asked for the confirmation of whether the derived datatypes are correct.
Thank you very much!
The system: Python 3.6 pycaret 2.3 CentOS 7 PyCharm 2020.1 Community Edition
My code:
regression.setup(data=ml_df,
target='occupation',
n_jobs=6,
categorical_features=['cluster', 'vacation', 'long_weekend', 'month', 'hour', 'weekday'],
numeric_features=['temperature', 'precipitation'],
silent=False
)
best_regression_models = regression.compare_models()
categorisation = [
[-0.1, 'empty'],
[0.01, 'partial'],
[0.99, 'full']
]
ml_df['occupation'] = modelling_utils.convert_number_to_categorical(ml_df['occupation'], categorisation)
classification.setup(data=ml_df,
target='occupation',
n_jobs=6,
categorical_features=['cluster', 'vacation', 'long_weekend', 'month', 'hour', 'weekday'],
numeric_features=['temperature', 'precipitation'],
fix_imbalance=True,
silent=False)
best_classification_models = classification.compare_models()
The full output is somewhat lengthy and saved here.
Edit: The code works as expected in a Jupyter Notebook