Multiobjective Multiclass And Multilabel Data Classification With Class Imbalance Theory And Practices 1st Edition Sanjay Chakraborty by Sanjay Chakraborty, Lopamudra Dey 9789819796212, 9819796210 instant download after payment.

In the ever-evolving landscape of machine learning, the challenges of multi-objective, multi-class, and multi-label data classification are becoming increasingly critical, especially in the presence of data imbalance. This book delves into the intricacies of these advanced classification problems, providing a comprehensive exploration of methodologies, algorithms, and real-world applications. By addressing the unique difficulties posed by data imbalance, we offer practical solutions and innovative approaches to enhance model performance and accuracy. Whether you are a researcher, data scientist, or practitioner, this book aims to equip you with the knowledge and tools necessary to navigate and excel in the complex domain of multi-objective and multi-label classification, ultimately fostering a deeper understanding and more effective handling of diverse and imbalanced datasets. This book is divided into six chapters.