evaluate | GridSearch | Hyperparameter Tuning in 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
March 2024
Language
English (United States)
Last Update
2024-10-10
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lifecycle
latest
Product Category
Teradata Vantage

Use the evaluate() method for evaluation using trained models from Analytics Database, VAL, and UAF features.

Evaluation are done using the default trained model.

  • Evaluation is supported for evaluable model-trainer functions.
  • Best model is set as default model by default.
  • Default model can be changed using set_model method.

Optional Arguments:

  • kwargs: Specifies the keyword arguments. Accepts additional arguments required for the teradataml analytic function evaluations.

    If this argument is empty, internal sampled test dataset and arguments are used for evaluation. Otherwise, all arguments required with validation data need to be passed for evaluation.

Output teradataml DataFrames can be accessed using attribute references, such as HPTEvaluateObj.<attribute_name>. Output teradataml DataFrame attribute name is: result.