Binary vs Multiclass Classification

The video tutorial explains the difference between binary and multiclass classification problems. Binary classification involves two classes, while multiclass classification involves more than two. The video provides examples, such as predicting fruit types or weather outlooks, to illustrate multiclass classification. It also discusses the importance of choosing the right classification algorithms, noting that some are designed for binary tasks but can be adapted for multiclass problems using heuristic methods like one-vs-rest and one-vs-one. The video emphasizes understanding these methods to effectively apply them in machine learning models.

How does logistic regression handle multiclass classification?

What are the heuristic methods mentioned for splitting multiclass classification problems?