Re-examining Model Evaluation: The CRISP Approach - Machine Learning Times - machine learning & data science news
Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
SHARE THIS:

2 months ago
Re-examining Model Evaluation: The CRISP Approach

 The performance of prediction models can be judged using a variety of methods and metrics. Some years ago, I was challenged to arrive at a set of rules that would provide both the analyst and marketer guidance as to how to evaluate results of a predictive modeling exercise. “What?” you ask.  “Just look into a standard textbook, and a whole host of criteria is readily available.”  These provide value to a more quantitative oriented manager, but to the novice marketer, these evaluation tools can be intimidating. After all, a ROC curve, a  Kolmogorov Smirnov test, or a  Root Mean Squared

To view this content
Login OR subscribe for free

Already receive the Machine Learning Times emails?
The Machine Learning Times now requires legacy email subscribers to upgrade their subscription - one time only - in order to attain a password-protected login and gain complete access.

Click here to complete this one-time subscription upgrade

Existing Users Log In
   
New User Registration
*Required field

Comments are closed.

Pin It on Pinterest

Share This