What is the purpose of extreme multi label classification?

Extreme multi-label classification is a field within machine learning that focuses on predicting multiple relevant labels for a given input sample. The purpose of extreme multi-label classification is to solve problems where the number of possible labels is extremely large, reaching into the thousands or even potentially millions. This type of classification is particularly useful in various real-world applications, such as recommendation systems, natural language processing, and web search. By accurately predicting multiple labels, extreme multi-label classification enables more precise and personalized recommendations, improving user experiences and expanding the capabilities of machine learning algorithms in handling complex tasks.

This mind map was published on 11 July 2023 and has been viewed 100 times.