Predicting Tags for Stackoverflow Questions Through A Multi-Class Multi-Tag Classifier System

Abstract

This work approaches the contest “Stack Overflow Tag Prediction” published on Kaggle website. The challenge is to identify suitable tags for question on StackOverflow. This can be termed as a multi-class multi-tag classification problem, as a question can come under different topics and also have several tags. The solution proposed is three – way classifier system where the question is assumed to have a maximum of three tags. To understand the feasibility of this method we used 3 models of classification namely - SVM, Naïve Bayes and Logistic Regression and compared the results using certain score metrics.