save model and load model function in clustering in pycaret

Recipe Objective - What is the save_model, load_model function in the clustering model in pycaret?

PyCaret provides save_model and load_model in the clustering module.

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Save model function with Example:-

PyCaret provides "pycaret.clustering.save_model()" function.

The Save model function saves the transformation pipeline and trained model object into the current working directory as a pickle file for later use.

from pycaret.datasets import get_data
jewll = get_data('jewellery')
# importing clustering module
from pycaret.clustering import *
# initialize the setup
setup_name = setup(data = jewll)
# k_means clustering
k_m = create_model('kmeans')
# saving model
save_model(k_m, 'saved_kmean_model')


load_model function with Example:-

PyCaret provides "pycaret.clustering.load_model()" function.

The load model function loads a previously saved pipeline.

from pycaret.clustering import load_model
saved_km = load_model('saved_kmean_model')
saved_km