[PDF.29wt] Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie)

Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie)

[PDF.je76] Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie)

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 | #1245419 in Books |  Chapman and Hall/CRC |  2012-06-06 | Original language:English | PDF # 1 |  9.21 x.56 x6.14l,1.05 | File type: PDF | 236 pages

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||1 of 2 people found the following review helpful.| not worth it|By Mikhail|PROS:
- nice cover
CONS:
- no gradient boosting machines (GBM)
- no proofs
- no state of art methods
- only high level overview of some old methods
- overpriced|2 of 7 people found the following review helpful.| This is also a great book for industry practitioners of ensemble tech| ||"… a valuable contribution to theoretical and practical ensemble learning. The material is very well presented, preliminaries and basic knowledge are discussed in detail, and many illustrations and pseudo-code tables help to understand the facts of thi

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field.

After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging...

You can specify the type of files you want, for your device.Ensemble Methods: Foundations and Algorithms (Chapman & Hall/CRC Data Mining and Knowledge Discovery Serie)   |  Zhi-Hua Zhou. Which are the reasons I like to read books. Great story by a great author.

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