Hybrid classifiers: methods of data, knowledge, and classifier combination

摘要

This book is directed to machine learning (ML) students, researchers, and practitioners searching for a better understanding of different concepts and techniques adopted in data and knowledge manipulation and classification. It is especially useful for those looking for better methods, better solutions, and new ways of applying combined classifiers, multiple classifiers, ensemble classifiers, classifier fusion, data stream classifiers, and hybrid machine learning methods. All of these methods are used for data and knowledge integration, transformation, classification, evaluation, and use. The author presents an up-to-date review of recent advances in this area.