pycaret.clustering.assign_model

pycaret.clustering.assign_model(model, transformation: bool = False, verbose: bool = True) → DataFrame

This function assigns cluster labels to the dataset for a given model.

Example

>>> from pycaret.datasets import get_data
>>> jewellery = get_data('jewellery')
>>> from pycaret.clustering import *
>>> exp_name = setup(data = jewellery)
>>> kmeans = create_model('kmeans')
>>> kmeans_df = assign_model(kmeans)

model: scikit-learn compatible object

Trained model object

transformation: bool, default = False

Whether to apply cluster labels on the transformed dataset.

verbose: bool, default = True

Status update is not printed when verbose is set to False.

Returns:

pandas.DataFrame