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preparation data for churn prediction #76

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maksimusGREEN opened this issue Jan 24, 2022 · 1 comment
Open

preparation data for churn prediction #76

maksimusGREEN opened this issue Jan 24, 2022 · 1 comment

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@maksimusGREEN
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Hello!
Thank you for the materials!

Please, can you help with advise?

I am trying to solve churn prediction task. I have 12 timestamp (month) time-series for 500000 customers with some features.
I have churn event for some customers, and some of customers don't have event among whole history.
Is it correct, if i do follow definition of targets:
For customers, who have an event:
event: [0,0,0,0,0,0,0,1,0,0,0,0]
tte: [7,6,5,4,3,2,1,0,4,3,2,1]
u: [1,1,1,1,1,1,1,1,0,0,0,0]
For customers, who don't have an event:
event: [0,0,0,0,0,0,0,0,0,0,0,0]
tte:[12,11,10,9,8,7,6,5,4,3,2,1]
u:[1,1,1,1,1,1,1,1,1,1,1,1]

Did i make a mistake by definition the target in this way?

How I should, if it is wrong?
Thank you!

@ktncktnc
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I met the same problem. Can someone help us?

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