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Machine Learning and Knowledge Discovery in Databases, Wray Buntine; Marko Grobelnik; Dunja Mladenic; Joh


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Автор: Wray Buntine; Marko Grobelnik; Dunja Mladenic; Joh
Название:  Machine Learning and Knowledge Discovery in Databases
ISBN: 9783642041730
Издательство: Springer
Классификация:







ISBN-10: 3642041736
Обложка/Формат: Paperback
Страницы: 762
Вес: 1.20 кг.
Дата издания: 2009
Серия: Lecture Notes in Computer Science
Язык: English
Иллюстрации: Biography
Размер: 236 x 158 x 31
Читательская аудитория: Professional & vocational
Подзаголовок: European conference, ecml pkdd 2009, bled, slovenia, september 7-11, 2009, proceedings
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009.


Machine Learning and Knowledge Discovery in Databases

Автор: Berendt
Название: Machine Learning and Knowledge Discovery in Databases
ISBN: 3319461303 ISBN-13(EAN): 9783319461304
Издательство: Springer
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Цена: 8106.00 р.
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Описание: The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 8695.00 р.
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Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>

Scaling up Machine Learning

Автор: Bekkerman
Название: Scaling up Machine Learning
ISBN: 0521192242 ISBN-13(EAN): 9780521192248
Издательство: Cambridge Academ
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Цена: 14731.00 р.
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Описание: In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a variety of machine learning methods developed specifically for parallel or distributed systems, covering algorithms, platforms and applications.

Statistical and Machine-Learning Data Mining

Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 9033.00 р.
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Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Foundations of Data Mining and Knowledge Discovery

Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi
Название: Foundations of Data Mining and Knowledge Discovery
ISBN: 364243228X ISBN-13(EAN): 9783642432286
Издательство: Springer
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Цена: 27251.00 р.
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Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.

Data Warehousing and Knowledge Discovery

Автор: Il-Yeol Song; Johann Eder; Tho Manh Nguyen
Название: Data Warehousing and Knowledge Discovery
ISBN: 3540858350 ISBN-13(EAN): 9783540858355
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Includes the refereed proceedings of the 10th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2008, held in Turin, Italy, in September 2008. This book contains 40 papers that were selected from 143 submissions.

Machine Learning and Knowledge Discovery in Databases

Автор: Frasconi
Название: Machine Learning and Knowledge Discovery in Databases
ISBN: 3319462261 ISBN-13(EAN): 9783319462264
Издательство: Springer
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Цена: 13696.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016.

Machine Learning and Knowledge Discovery in Databases

Автор: Frasconi
Название: Machine Learning and Knowledge Discovery in Databases
ISBN: 3319461273 ISBN-13(EAN): 9783319461274
Издательство: Springer
Рейтинг:
Цена: 13696.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016.

Machine Learning and Knowledge Discovery in Databases

Автор: Wray Buntine; Marko Grobelnik; Dunja Mladenic; Joh
Название: Machine Learning and Knowledge Discovery in Databases
ISBN: 3642041795 ISBN-13(EAN): 9783642041792
Издательство: Springer
Рейтинг:
Цена: 18167.00 р.
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Описание: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009.

Advances in Knowledge Discovery and Management

Автор: Fabrice Guillet; Bruno Pinaud; Gilles Venturini
Название: Advances in Knowledge Discovery and Management
ISBN: 3319457624 ISBN-13(EAN): 9783319457628
Издательство: Springer
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Цена: 16769.00 р.
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Описание:

This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks.
Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.
Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery

Автор: Walter W. Piegorsch
Название: Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery
ISBN: 111903065X ISBN-13(EAN): 9781119030652
Издательство: Wiley
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Цена: 2685.00 р.
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Описание: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery.

Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
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Описание:

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
  • Includes open-access online courses that introduce practical applications of the material in the book

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