Saving and loading model

When you have lots of data and training takes a lot of time option with saving and loading model could be useful. First you need to fit the model, then save it and load.

Fit model

from lifetimes import BetaGeoFitter
from lifetimes.datasets import load_cdnow_summary

data = load_cdnow_summary(index_col=[0])
bgf = BetaGeoFitter()
bgf.fit(data['frequency'], data['recency'], data['T'])
bgf
"""<lifetimes.BetaGeoFitter: fitted with 2357 subjects, a: 0.79, alpha: 4.41, b: 2.43, r: 0.24>"""

Saving model

Model will be saved with dill to pickle object. Optional parameters save_data and save_generate_data_method are present to reduce final pickle object size for big dataframes. Optional parameters:

• save_data is used for saving data from model or not (default: True).
• save_generate_data_method is used for saving generate_new_data method from model or not (default: True)

bgf.save_model('bgf.pkl')

or to save only model with minumum size without data and generate_new_data:

bgf.save_model('bgf_small_size.pkl', save_data=False, save_generate_data_method=False)

Loading model

Before loading you should initialize the model first and then use method load_model

bgf_loaded = BetaGeoFitter()
bgf_loaded.load_model('bgf.pkl')
bgf_loaded
"""<lifetimes.BetaGeoFitter: fitted with 2357 subjects, a: 0.79, alpha: 4.41, b: 2.43, r: 0.24>"""