Machine Learning: ECML 2006 : 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings

Johannes Fürnkranz

ISBN 10: 354045375X / ISBN 13: 9783540453758

Editore: Springer, Berlin, Springer, 2006

Riguardo questo articolo

Neuware - This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held, jointly with PKDD 2006. The book presents 46 revised full papers and 36 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers present a wealth of new results in the area and address all current issues in machine learning.

Codice articolo 9783540453758

Dati bibliografici

• Titolo: Machine Learning: ECML 2006 : 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings
• Editore: Springer, Berlin, Springer
• Data di pubblicazione: 2006
• Lingua: Inglese
• ISBN 10: 354045375X
• ISBN 13: 9783540453758
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 35 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 35 millimetri di profondità
• Peso: 1306 grammi

Descrizione articolo

Riassunto

This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held, jointly with PKDD 2006. The book presents 46 revised full papers and 36 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers present a wealth of new results in the area and address all current issues in machine learning.

Recensione

From the reviews:

"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)