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Book synopsis

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 direction.

Book details

Book category Books in English Computing & information technology Computer science Artificial intelligence

• Full title: Imbalanced Learning - Foundations, Algorithms, and Applications
• Author: Haibo He, Yunqian Ma
• Language: English
• Binding: Hardback
• Number of pages: 216
• EAN: 9781118074626
• ISBN: 1118074629
• ID: 01401752
• Publisher: John Wiley & Sons Inc
• Weight: 502 g
• Dimensions: 242 × 166 × 18 mm
• Date of publishing: 09. August 2013

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