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
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Enterprise_2000
- lifecycle
- latest
- Product Category
- Teradata Vantage
- teradataml.hyperparameter_tuner.optimizer.RandomSearch.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