Multi-objective, Multi-class and Multi-label Data Classification with Class Imbalance

Theory and Practices
2025
ISBN: 978-981-97-9621-2
Verlag: Springer Nature Singapore

Buch, Englisch, 164 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 479 g

Reihe: Springer Tracts in Nature-Inspired Computing

This book explores intricate world of data classification with 'Multi-Objective, Multi-Class, and Multi-Label Data Classification.' This book studies sophisticated methods and strategies for working with complicated data sets, tackling the difficulties of various classes, many objectives, and complicated labelling tasks. This resource fosters a deeper grasp of multi-dimensional data analysis in today's data-driven world by providing readers with the skills and insights needed to navigate the subtleties of modern classification jobs, from algorithmic techniques to practical applications.

Zielgruppe

Research

Autoren/Hrsg.

Dey, Lopamudra

Chakraborty, Sanjay

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. Introduction to Classification.- 2. Class Imbalance and Data Irregularities in Classification.- 3. Multi-class Classification.- 4. Multi-Objective and Multi-Label Classification.- 5. Deep Learning Inspired Multiclass and Multilabel Classification.- 6. Applications of Multi-objective, Multi-label and Multi-class Classifications.

Über Autor(innen)

Dr. Sanjay Chakraborty received his Ph.D. at the University of Calcutta, India. He received his Master of Technology from the National Institute of Technology Raipur, India. He is currently working as a Postdoc Researcher with the Department of Computer and Information Science (IDA), REAL, AIICS, Linköping University, Sweden and Associate Professor (lien) at Techno International New Town, Kolkata, India. He has published 70 research papers in various international journals, conferences, and book chapters. He has published three internationally authored books and five patents. His areas of interest are machine learning, applied AI, and quantum computing. He has a total of 14 years of teaching and research experience. He is an active Member of the board of reviewers in various International Journals, IEEE Transactions, and Conferences. He also achieved the top five best paper recognition by ASEJ, Elsevier, and the most cited author award from Biomedical Journal, Elsevier, in 2021.

Dr. Lopamudra Dey completed her B-Tech from West Bengal University of Technology, Kolkata, India in Computer Science and Engineering in 2009. She received a Bronze medal in her bachelor's degree. In 2011, she completed her Master of Technology from the University of Kalyani, West Bengal India. She obtained her Ph.D. in Computer Science and engineering from Kalyani University in 2021. She is currently working as an Associate Professor in the Department of Computer Science and Engineering at Meghnad Saha Institute of Technology, Kolkata, India. She has a total of 14 years of teaching and research experience. Her areas of interest include Bioinformatics, Data Mining, and Network Security. She has published over 45 research articles in journals, conferences, and book chapters. She is also the author of an international book. She received the most cited author award from the Biomedical Journal, Elsevier, in 2021.