AutoML Setup and Requirements | Teradata Package for Python - AutoML Setup and Requirements - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
VMware
Enterprise
IntelliFlex
Product
Teradata Package for Python
Release Number
20.00
Published
March 2025
ft:locale
en-US
ft:lastEdition
2026-02-20
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Product Category
Teradata Vantage

AutoML depends on the Python packages imbalanced-learn and scikit-learn. Use the following command to install these packages before running AutoML.

pip install teradataml[automl]

AutoCluster leverages open-source machine learning functions for model training, which requires the appropriate cluster configuration to ensure full support of these capabilities. For detailed guidance, see teradataml OpenSourceML Setup and Requirements.

AutoCluster is currently supported only on Python versions 3.8 and 3.11.

Pandas version support

AutoML is currently supported with pandas 2.x only.

pandas 3.0 and above are not supported at this time.

To ensure successful execution of AutoML workflows, use:

pandas >= 2.0 and < 3.0

scikit-learn version support

Feature selection using Lasso is currently supported up to scikit-learn 1.7.2.

For scikit-learn 1.8 and above, you must either disable Lasso-based feature selection or downgrade scikit-learn to version 1.7.2 to run AutoML successfully.