Including Association Analysis results into existing Classification Model


I have trained a classification model that predicts (returns a score) on how likely a customer is to buy from our company. This model does not contain any product specific data, but we nevertheless apply it when determining which are the most likely customers to buy a certain product, e.g. product A (of course the results we get are the same if we use the model for product A,B,C...).

Additionally, we have performed Association Analysis on the Customer/Products set and have come up with certain rules (e.g. customer buying product C is more likely to buy A) and have computed the respective lifts for these rules.

Is there a way to use the information derived in the Association Analysis to systematically "enhance" the use of our classification model?

An example to illustrate this would be the following.

Suppose that, according to our Classification Model, these are the most likely customers to buy product A:

  • Customer X (score 9.0)
  • Customer Y (score 9.0)
  • Customer Z (score 8.0)

Additionally, suppose that we have the following rule with a lift of 1.2: B => A. If customer Y has bought product B (but X hasn't), it would be logical to increase customer's Y score.

Why should this post be closed?


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