Multi-label Classification Problems with Large Langage Models
In today's data-driven world, accurately categorizing information has become crucial. The task of multi-label classification, where data can belong to multiple categories simultaneously, addresses this need effectively. Unlike traditional single-label classification, multi-label classification mirrors the complexity of real-world data and often comes to the forefront in wider data analysis efforts.