BookmarkSubscribeRSS Feed
Ullsokk
Pyrite | Level 9

I have several Gradient Boosting models in production. I have gotten requests from users of the final score\model of beeing able to get insight into why a customer has a high probability of an outcome, say churn or buying a product. 

 

Showing which variables are important in a model, along with the customers variables could of course bring some insight for a trained statistician\data scientist, but that hardly helps an untrained eye. 

 

Is there any smart way of explaining why one customer gets a high score? I picture a stored process that takes a given customer as input, and outputs some report that shows some of the most important drivers of the customers score. This can of course be exceedingly complex in such a model, but have you seen any attempts at it?

1 REPLY 1

hackathon24-white-horiz.png

The 2025 SAS Hackathon has begun!

It's finally time to hack! Remember to visit the SAS Hacker's Hub regularly for news and updates.

Latest Updates

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 807 views
  • 1 like
  • 2 in conversation