evaluate | AutoML | teradataml - evaluate - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
December 2024
ft:locale
en-US
ft:lastEdition
2025-01-23
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nvi1706202040305.ditamap
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plt1683835213376.ditaval
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rkb1531260709148
Product Category
Teradata Vantage

Use the evaluate() function to evaluate on data using model rank in leaderboard and generate performance metrics. Returns DataFrame with performance metrics.

Raises TeradataMlException.

If both fit and load methods are called before predict, then fit method model will be used for prediction by default unless 'use_loaded_models' is set to True in predict.
Required argument:
  • data specifies the dataset on which performance metrics needs to be generated.

    Types: teradataml DataFrame

    Target column used for generating model is mandatory in data for evaluation.
Optional arguments:
  • rank specifies the rank of the model available in the leaderboard to be used for evaluation.

    Default value: 1

    Types: int

  • use_loaded_models specifies whether to use loaded models from database for prediction or not.

    Default value: False

    Types: bool