A lightweight filter based feature selection approach for multi-label text classification

• Published in: Journal of ambient intelligence and humanized computing Vol. 14; no. 9; pp. 12345 - 12357
• Main Authors: Dhal, Pradip, Azad, Chandrashekhar
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2023; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Classification; Computational Intelligence; Engineering; Feature extraction; Labels; Lightweight; Machine learning; Multilayer perceptrons; Multilayers; Natural language processing; Optimization; Original Research; Robotics and Automation; Set theory; Text categorization; User Interfaces and Human Computer Interaction; Weighting; Multi-label text classification; multi-layer perceptron; chi-square based feature selection

Multi-label Text Classification (MTC) is a challenging task in Natural Language Processing (NLP). The goal of the MTC task is to label a document with a set of labels. By incorporating various term weighting schemes in MTC, high dimensional feature space has been generated; due to that, multi-label...