ywu-stats
ywu-stats
Having the same question here. If I have the discount_rate=0, is future CLV= predicted_puchases * conditional_expected_average_profit ?
Here is an example with my real data: frequency_cal: 20 recency_cal: 482days T_cal: 500days monetary_value_cal :74$ frequency_holdout:21 monetary_value_holdout:39$ duration_holdout: 365 days predicted_purchases: 12 days predicted_monetary_value: ```py ggf.conditional_expected_average_profit(( data['frequency_cal'], data['monetary_value_cal'] ))...
Now you can tell how badly I wanted to make use of this. So now I'm trying to figure out in each of the clusters, which userid are in it...
Thank you for the information! I'm indeed learning Python recently :) Another question I have is that where can I change the length of ngrams? I remember in your publication...
Hmmm...seems like it's the predefined input structure? Then I do want to clarify something about the methodology in the publication. My understanding was, the whole feature space is a union...
I see, thanks!