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.

AIML.com

Machine Learning Resources

Why is Random Forest a non-linear model? Why does it result in non-linear decision boundaries?

Bookmark this question

Random Forest is a non-linear model because it does not assume a linear relationship between the target and predictor variables. The non-linearity of Random Forest, or even a single decision tree, can be illustrated by the box-like decision boundary that results from the training of the model. For instance, it is possible for the same feature to be used in different splitting criteria within different levels of a decision tree. As a result, the algorithm is able to learn complex relationships present within the data structure without being subject to the constraints and assumptions of a linear model. 

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 | LearnEngine.com