lifetimes
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CamDavidsonPilon
Lifetime value in Python
I know the library easily plots them on a beautiful heatmap. but what is the logic behind getting that data of dead and alive customers
"conditional_probability_alive" computes the probability that a customer with history (frequency, recency, T) is currently alive.. Is there a method to find the probability that a customer will be alive after...
Quick question: How come the `conditional_probability_alive` doesn't return a dataframe that shows the customer ID with the probability? Is it safe to append it to the summary dataframe?
Hi, Can we modify the assumption such that we can consider a time varying gamma in the Poisson distribution? It seems more realistic to have a time varying gamma over...
Is there any documentation available / comments that can be added explaining the rationale for calculation of ln_hyp_term_alt when ln_hyp_term is inf (lines 244 to 249) ? I am asking...
Dear Sir, While testing BG/BB models, I came across the following error when calling `plot_period_transactions` to verify the fitting results ```py TypeError: unsupported operand type(s) for +: 'int' and 'list'...
If I look at the examples for the p_active history for a customer, I see this chart:  What's the intuition as to why p_active is less than 1 on...
The logic is averaging the individual line items in the holdout period when calculating monetary_value_holdout column. For the calibration period, monetary value is calculated by summing the monetary value for...
Hi, I'm using `customer_lifetime_value` to calculate CLV and I get RMSE of ~0.4 (which I think is good). The problem is that I found users that have CLV lower than...
Dear Cameron, It looks like there is another casting issue for newer version of python/pandas plot_history_alive failed with TypeError : can't multiply sequence by non-int of type 'numpy.float64' ``` Traceback...