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I'm trying to build a regression model, where I see which attributes are influencing the margin. My data set looks like something below.

UserId  |  [products_bought] | revenue |  [places_visited] | discount  --> Margin

In the above mentioned schema a single user might have bought a set of products maximum of 4000 and places visited can be in hundreds.

I tried to flatten the data but this is very sparse, are there any approaches to efficiently model this kind of problem

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  • $\begingroup$ Do you have revenue per product, or just total revenue for each customer? $\endgroup$
    – Paul
    Commented Jan 31, 2017 at 13:40
  • $\begingroup$ @Paul I've total revenue per customer not at product level $\endgroup$
    – tourist
    Commented Jan 31, 2017 at 15:02

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