The website is in Maintenance mode. We are in the process of adding more features.
Any new bookmarks, comments, or user profiles made during this time will not be saved.

Machine Learning Resources

What is Feature Binarization? When to use feature binarization?

Bookmark this question

This refers to a special case of discretization in which a continuous variable is transformed into a categorical representation that only consists of two bins. Thus, a dummy variable is essentially created, where one bin represents the “on” level and the other the “off” or reference level. This approach works well when there is a near dichotomous threshold that separates observations in relation to the target and also adds fewer dimensions to the feature space compared to if more bins are created. 

Leave your Comments and Suggestions below:

Please Login or Sign Up to leave a comment

Partner Ad  

Find out all the ways
that you can

Explore Questions by Topics

Partner Ad

Learn Data Science with Travis - your AI-powered tutor |