Teradata Package for Python Function Reference | 20.00 - best_model - 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.best_model
DESCRIPTION:
    Returns the best trained model obtained from hyperparameter tuning.
    Note:
        "best_model" is not supported for non-model trainer functions.
 
RETURNS:
    object of trained model.
 
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.
    >>> # Retrieve the best model.
    >>> optimizer_obj.best_model
        ############ output_data Output ############
 
           iterNum      loss       eta  bias
        0        3  2.060386  0.028868   0.0
        1        5  2.055509  0.022361   0.0
        2        6  2.051982  0.020412   0.0
        3        7  2.048387  0.018898   0.0
        4        9  2.041521  0.016667   0.0
        5       10  2.038314  0.015811   0.0
        6        8  2.044882  0.017678   0.0
        7        4  2.058757  0.025000   0.0
        8        2  2.065932  0.035355   0.0
        9        1  1.780877  0.050000   0.0
 
 
        ############ result Output ############
 
                                 predictor    estimate       value
        attribute
         7                        Latitude    0.155095        None
        -9         Learning Rate (Initial)    0.050000        None
        -17                   OneClass SVM         NaN       FALSE
        -14                        Epsilon    0.100000        None
         5                      Population    0.000000        None
        -12                       Nesterov         NaN        TRUE
        -5                             BIC   73.297397        None
        -7                           Alpha    0.500000  Elasticnet
        -3          Number of Observations   55.000000        None
         0                     (Intercept)    0.000000        None