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Toxic comment classification has become an active research field with many recently proposed approaches. However, while these approaches address some of the task’s challenges others still remain unsolved and directions for further research are needed. To this end, we compare different machine learning, deep learning and shallow approaches on a new…
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Poster.pdf
README.md
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logistic approach.ipynb
lstm approach.py
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readMe.txt
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README.md

Multi-Label-Text-Classification

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.

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.
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