Machine Learning: ECML 2006 - 2006

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Machine Learning: ECML 2006

Crossref Citations Summary

Crossref Citations by year

Crossref Citations by Chapter

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Mendeley readership by country

This book has 1109 Mendeley readers (combined total for all chapters).
Click here to see more details on the Mendeley website.

Country %
United States 121 11%
France 99 9%
United Kingdom 40 4%
Germany 30 3%
China 30 3%
Spain 25 2%
Brazil 15 1%
Italy 13 1%
Canada 13 1%
Poland 12 1%
Other 128 12%
Unknown 583 53%

Mendeley readership by discipline

Discipline %
Computer Science 749 68%
Engineering 124 11%
Agricultural and Biological Sciences 43 4%
Mathematics 37 3%
Computer and Information Science 24 2%
Other 128 12%
Unknown 4 0%

Mendeley readership by professional status

Professional status %
Student > Ph. D. Student 378 34%
Researcher 212 19%
Student > Master 182 16%
Student > Bachelor 72 6%
Professor > Associate Professor 51 5%
Other 210 19%
Unknown 4 0%

SpringerLink Download summary


  • "In this book, we find many ways of representing machine learning from different fields, including active learning, algorithmic learning, case-based learning, classifier systems, clustering algorithms, decision-tree learning, inductive inference, kernel methods, knowledge discovery, multiple-instance learning, reinforcement learning, statistical learning, and support vector machines. Most of the current issues in machine learning research are discussed. … I strongly recommend this book for all researchers interested in the very best of machine learning studies."

    Agliberto Cierco, ACM Computing Reviews, Vol. 49 (5), 2008