Teradata Package for Python Function Reference | 20.00 - predict - 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 - 20.00

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
2024-04-10
dita:id
TeradataPython_FxRef_Enterprise_2000
Product Category
Teradata Vantage
teradataml.hyperparameter_tuner.optimizer.GridSearch.predict = predict(self, **kwargs)
DESCRIPTION:
    Function uses model training function generated models from SQLE, 
    VAL and UAF features for predictions. Predictions are made using 
    the best trained model. Predict function is not supported for
    non-model trainer function.
 
PARAMETERS:
    kwargs:
        Optional Argument.
        Specifies the keyword arguments. Accepts all merge model 
        predict feature arguments required for the teradataml 
        analytic function predictions.
 
RETURNS:
    Output teradataml DataFrames can be accessed using attribute
    references, such as HPTObj.<attribute_name>.
    Output teradataml DataFrame attribute name is:
        result
 
RAISES:
    TeradataMlException, TypeError, ValueError
 
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 prediction using "optimizer_obj".
    >>> optimizer_obj.predict(newdata=test_data, **eval_params)
             id  prediction  MedHouseVal
        0   686    0.202843        1.578
        1  2018    0.149868        0.578
        2  1754    0.211870        1.651
        3   670    0.192414        1.922
        4   244    0.247545        1.117