One-vs-One (OvO) Heuristic Method

The video tutorial explains binary classification algorithms for multiclass classification, focusing on the one-vs-rest and one-vs-one strategies. It details how one-vs-one splits a multiclass problem into multiple binary problems, providing an example with four classes. The tutorial also covers the voting mechanism used in one-vs-one and discusses the practical application of these strategies. It concludes by mentioning alternative algorithms that inherently support multiclass classification, such as decision trees and random forests.

What happens when a new data input is introduced to the classifiers in the one versus one strategy?

Which algorithms can be used that support multiclass classification without worrying about the binary approaches?