Teradata Package for Python Function Reference on VantageCloud Lake - evaluate - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.hyperparameter_tuner.optimizer.GridSearch.evaluate = evaluate(self, **kwargs)
- DESCRIPTION:
Function uses trained models from SQLE, VAL and UAF features for
evaluations. evaluations are made using the default trained model.
Notes:
* Evaluation supported for evaluatable model-trainer functions.
* Best model is set as default model by default.
* Default model can be changed using "set_model()" method.
PARAMETERS:
kwargs:
Optional Argument.
Specifies the keyword arguments. Accepts additional arguments
required for the teradataml analytic function evaluations.
While "kwargs" is empty then internal sampled test dataset
and arguments used for evaluation. Otherwise,
All arguments required with validation data need to be passed
for evaluation.
RETURNS:
Output teradataml DataFrames can be accessed using attribute
references, such as HPTEvaluateObj.<attribute_name>.
Output teradataml DataFrame attribute name is:
result
RAISES:
TeradataMlException
EXAMPLES:
>>> # Create an instance of the search algorithm called "optimizer_obj"
>>> # by referring "__init__()" method.
>>> # Perform "fit()" method on the optimizer_obj to populate model records.
>>> # Perform evaluation using best model.
>>> optimizer_obj.evaluate(newdata=test_data, **eval_params)
############ result Output ############
MAE MSE MSLE MAPE MPE RMSE RMSLE ME R2 EV MPD MGD
0 2.616772 8.814968 0.0 101.876866 101.876866 2.969001 0.0 5.342344 -4.14622 -0.14862 NaN NaN