Imbalanced learning : foundations, algorithms, and applications /

• Other Authors: He, Haibo, 1976- (Editor), Ma, Yunqian (Editor)
• Format: eBook
• Language: English
• Published: Hoboken, New Jersey : John Wiley & Sons, Inc., [2013]
• Subjects: Data mining.; Information resources > Evaluation.; Information resources management.; System analysis > Mathematical models.; COMPUTERS > Database Management > Data Mining.; Electronic books.
• Physical Description: 1 online resource.
• Bibliography: Includes bibliographical references and index.
• ISBN: 9781118646335; 1118646339; 9781118646205; 1118646207; 9781118646274; 1118646274; 9781118646106; 111864610X; 1118074629; 9781118074626; 9781299665118; 129966511X
• DOI: 10.1002/9781118646106

Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, and defense, to name a few. The first comprehensive look at this new branch of machine learning, this volume offers a critical review of the problem of imbalanced learning, covering the state-of-the-art in techniques, principles, and real-world applications. Scientists and engineers will learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research.