- Single model generation in VantageCloud Enterprise and VantageCloud Lake might reach memory limits when trained on very large data.
- split() function of model_selection module returns generator of train and test data when used locally with scikit-learn, but with teradataml OpenSourceML module, it returns generator of train and test as teradataml DataFrames.
- Functions like predict, transform, and so on, return only labels/predictions in scikit-learn. They return the features data along with labels/predictions in teradataml OpenSourceML.
- list and delete model in Model Operations are not supported.
- To list the deployed models, run DataFrame(“opensourceml_models”) or SELECT * FROM opensourceml_models.
- To delete the models, run SQL query to delete the rows from the table “opensourceml_models”.
- Classes that take generators, iterators, functions, and callable objects as arguments are not supported.
- feature_extraction module is not supported.
See attached Supportability Matrix for teradataml OpenSourceML - scikit-learn classes and functions support.