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predictive analytics customer-based product recommendations

matthias_komatthias_ko Member Posts: 1 Learner II
edited November 2018 in Help

 I want do some predictive analytics with rapidminer. My target is to predict the next best offer for each customer. Each line in my database includes customer_id and customer attributes as well as the columns with the subcategory and how often the customer bought products within the subcategory. So, now I think decision trees or regressions could be good algorithms.

Does anyone has some advice for me?

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Answers

  • Telcontar120Telcontar120 RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 Unicorn

    Decision Trees are good for classification tasks, but they are prone to overfitting, so be careful with them.  You may want to start with one for data understanding but then supplement with Random Forest or with Gradient Boosted Trees.

    Regression is for numerical labels, so it might not be the best approach for a next-best-offer problem.

     

    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
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