Decision tree to get difference in rates in two groups?

I have two sample groups of customers, each customer has 100s of features. For a single sample, i would use Decision Trees to find sub-groups that have a high churn rate. Thats easy.

However, my requirement is: between two samples (below), find segment(s) such that in one sample its churn rate is high and in the other, it is low. In other words, find a sub-group which has the highest difference in churn rate.

What is an appropriate algorithm to solve this?

Thanks.

Topic unsupervised-learning churn decision-trees predictive-modeling

Category Data Science

1
answered at

You can frame this issue as feature importance. Which features have the greatest influence on the target value of churn rate?

There are many ways to approach feature importance. In decision trees, permutation importance can be used.

About

Geeks Mental is a community that publishes articles and tutorials about Web, Android, Data Science, new techniques and Linux security.