lifetimes

comparison.py

# the real number of transactions in the observation period, which equals frequency_holdout + 1
rfm_cal_holdout["n_transactions_holdout_real"]  = rfm_cal_holdout["frequency_holdout"] + 1

# the predicted number of transactions in the next 26 weeks (length of the observation period)
rfm_cal_holdout["n_transactions_holdout_pred"] = bgf.predict(t=26, 
                                                    frequency=rfm_cal_holdout['frequency_cal'], 
                                                    recency=rfm_cal_holdout['recency_cal'], 
                                                    T=rfm_cal_holdout['T_cal'])

# comparison of the real and predicted transactions
rfm_cal_holdout[["n_transactions_holdout_real", "n_transactions_holdout_pred"]].head()