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Item Details
| Title:
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IMBALANCED LEARNING
FOUNDATIONS, ALGORITHMS, AND APPLICATIONS |
| By: |
Haibo He (Editor), Yunqian Ma (Editor) |
| Format: |
Hardback |
| List price:
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£107.95 |
| Our price: |
£97.16 |
| Discount: |
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| You save:
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£10.79 |
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| ISBN 10: |
1118074629 |
| ISBN 13: |
9781118074626 |
| Availability: |
Usually dispatched within 1-3 weeks.
 Delivery
rates
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| Stock: |
Currently 0 available |
| Publisher: |
JOHN WILEY & SONS INC |
| Pub. date: |
1 July, 2013 |
| Pages: |
216 |
| Description: |
Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, and defense, to name a few. |
| 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. |
| Illustrations: |
illustrations |
| Publication: |
US |
| Imprint: |
John Wiley & Sons Inc |
| Returns: |
Returnable |
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