save model and load model in anomaly detection in pycaret
This recipe explains the save model and load model in anomaly detection in pycaret. The Save model function saves the transformation pipeline in pickle file format and The load model function loads a previously saved pipeline.
Recipe Objective - What are save_model and load_model in anomaly detection in pycaret?
PyCaret provides save_model and load_model functions in the anomaly detection module.
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Save model function with Example:-
PyCaret provides "pycaret.anomaly.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
anmly = get_data('anomaly')
# importing anomaly module
from pycaret.anomaly import *
# initialize the setup
setup_name = setup(data = anmly)
# Knn model
knn = create_model('knn')
# saving model
save_model(knn, 'saved_knn_model')
load_model function with Example:-
PyCaret provides "pycaret.anomaly.load_model()" function.
The load model function loads a previously saved pipeline.
from pycaret.anomaly import load_model
saved_knn = load_model('saved_knn_model')
saved_knn
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