One Versus One vs. One Versus All in Classification Models

In this quick overview, we introduce you to the concepts of one-versus-one and one-versus-all in classification. In classification models, you will often want to predict one class from another. This is called binary classification, or one-versus-one. But what if you have more than two classes to predict? This is where one-versus-all is introduced. We will explain the difference between these two classification techniques, and describe scenarios where you may want to use one over the other.

Learn more about Classification Models:
Introduction to Classification Models
Introduction to the Confusion Matrix
Precision, Recall and F1 in Classification

Complete Series:
Data Science in Minutes

More Data Science Material:
[Video] Introduction to Text Analytics with R
[Video] Classification Models
[Blog] A Comprehensive Tutorial on Classification using Decision Trees


Rebecca Merrett
About The Author
- Rebecca holds a bachelor’s degree of information and media from the University of Technology Sydney and a post graduate diploma in mathematics and statistics from the University of Southern Queensland. She has a background in technical writing for games dev and has written for tech publications.


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