Teradata Package for Python Function Reference | 17.10 - delete_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
- Product
- Teradata Package for Python
- Release Number
- 17.10
- Published
- April 2022
- Language
- English (United States)
- Last Update
- 2022-08-19
- lifecycle
- previous
- Product Category
- Teradata Vantage
- teradataml.catalog.model_cataloging.delete_model = delete_model(name, delete_objects=False)
- DESCRIPTION:
Delete a model, and optionally delete the model objects.
A model can be deleted only by the creator of the model.
PARAMETERS:
name:
Required Argument.
Specifies the name of the model to be deleted.
Types: str
delete_objects:
Optional Argument.
Specifies whether to drop the model objects also.
When True, the model objects related to the model are deleted/dropped.
Types: bool
Default Value: False
RETURNS:
None.
RAISES:
TeradataMlException, TypeError, ValueError
EXAMPLES:
# Load the data to run the example
load_example_data("decisionforest", ["housing_train"])
# Create teradataml DataFrame objects.
housing_train = DataFrame.from_table("housing_train")
# The examples use home sales data to create a
# classification tree that predicts home style, which can be input
# to the DecisionForestPredict.
formula = "homestyle ~ driveway + recroom + fullbase + gashw + airco + prefarea + price + lotsize + bedrooms + bathrms + stories + garagepl"
rft_model = DecisionForest(data=housing_train,
formula = formula,
tree_type="classification",
ntree=50,
tree_size=100,
nodesize=1,
variance=0.0,
max_depth=12,
maxnum_categorical=20,
mtry=3,
mtry_seed=100,
seed=100
)
# Let's save this generated model.
save_model(model=rft_model, name="decision_forest_model", description="Decision Forest test")
# Example 1 - Only delete model information from the Model Catalog.
delete_model('decision_forest_model')
# Example 2 - Delete model information from the Model Catalog and drop model objects as well.
delete_model('decision_forest_model', True)