Deep dive into multi-label classification..! --Karthik Nooney

With continuous increase in available data, there is a pressing need to organize it and modern classification problems often involve the prediction of multiple labels simultaneously associated with a single instance.
Known as Multi-Label Classification, it is one such task which is omnipresent in many real world problems.
In this project, using a Kaggle problem as example, we explore different aspects of multi-label classification.
DISCLAIMER FROM THE DATA SOURCE: the dataset contains text that may be considered profane, vulgar, or offensive.

Bird’s-eye view of the project:


  • Part-1: Overview of multi-label classification.

  • Part-2: Problem definition & evaluation metrics.

  • Part-3: Exploratory data analysis (EDA).

  • Part-4: Data pre-processing.

  • Part-5: Multi-label classification techniques.



Click here to read more.