delete_data | AutoDataPrep in AutoML | teradataml - delete_data - Teradata VantageCloud Lake

Use the delete_data() function to delete the deployed datasets from the database.

Required Parameter

table_name

Specifies the name of the table containing the deployed datasets.

Optional Parameter

fs_method

Specifies the name of the feature selection method to delete from the deployed datasets.

Permitted values: "lasso", "rfe", "pca".

Default value: None

If "fs_method" is None, then the function deletes all the deployed datasets.

Example setup

Create an instance of the AutoDataPrep.

Fit the data.

Deploy the data to the table.

Remove the deployed data from the table.

Example 1: Remove the deployed data from the table within the AutoDataPrep object

from teradataml import AutoDataPrep

Load the example data.

>>> load_example_data("teradataml", "titanic")
    >>> titanic = DataFrame.from_table("titanic")

Create an instance of AutoDataPrep.

>>> aprep_obj = AutoDataPrep(task_type="Classification", verbose=2)

Fit the data.

>>> aprep_obj.fit(titanic, titanic.survived)

Deploy the data to the database.

>>> aprep_obj.deploy("table_name")

Remove lasso deployed data from the table.

>>> aprep_obj.delete_data("table_name", fs_method="lasso")

Example 2: Remove the deployed data from the table using different instance of AutoDataPrep object

Create an instance of AutoDataPrep.

>>> aprep_obj2 = AutoDataPrep()

Remove lasso and pca deployed data from the table.

>>> aprep_obj2.delete_data("table_name", fs_method=["lasso", "pca"])