Ensemble Methods by Zhi-Hua Zhou
Ensemble methods that train multiple learners and then combine them to use, with textit{Boosting} and textit{Bagging} as representatives, are well-known machine learning approaches. An ensemble is significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks.-
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Zhi-Hua Zhou, Professor of Computer Science and Artificial Intelligence at Nanjing University, President of IJCAI trustee, Fellow of the ACM, AAAI, AAAS, IEEE, recipient of the IEEE Computer Society Edward J. McCluskey Technical Achievement Award, CCF-ACM Artificial Intelligence Award.
| SKU | Unavailable |
| ISBN 13 | 9781032960609 |
| ISBN 10 | 1032960604 |
| Title | Ensemble Methods |
| Author | Zhi-Hua Zhou |
| Series | Chapman And Hall Crc Machine Learning And Pattern Recognition |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2025-03-10 |
| Number of pages | 348 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |