set_labels() | FeatureGroup Method | Teradata Package for Python - set_labels() - Teradata Package for Python

Use the set_labels() method to set labels for the FeatureGroup. This method is helpful when working with analytic functions to consume the features.

Required Parameter

labels

Specifies the names of the features to refer as labels.

Example setup

>>> from teradataml import DataSource, Entity, Feature, FeatureGroup, load_example_data
>>> load_example_data("dataframe", "admissions_train")

Create a DataFrame.

>>> df = DataFrame("admissions_train")

Create the features.

>>> masters_feature = Feature("masters", df.masters)
>>> gpa_feature = Feature("gpa", df.gpa)
>>> stats_feature = Feature("stats", df.stats)
>>> admitted_feature = Feature("admitted", df.admitted)

Create an entity.

>>> entity = Entity("id", df.id)

Create a data source.

>>> data_source = DataSource("admissions_source", df)

Create a feature group.

>>> fg = FeatureGroup('Admissions',
...                   features=[masters_feature, gpa_feature, stats_feature, admitted_feature],
...                   entity=entity,
...                   data_source=data_source)

Example 1: Set feature 'admitted' as label

Set the 'admitted' feature as the label.

>>> fg.set_labels('admitted')

True

Get the labels from the feature group.

>>> fg.labels

Feature(name=admitted)

Example 2: Set multiple features as labels

Set features 'masters' and 'gpa' as labels.

>>> fg.set_labels(['masters', 'gpa'])

True

Get the labels from the feature group.

>>> fg.labels

[Feature(name=masters), Feature(name=gpa)]