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Data Mining: Practical Machine Learning Tools and Techniques,, Ian H. Witten



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Автор: Ian H. Witten
Название:  Data Mining: Practical Machine Learning Tools and Techniques,
Перевод названия: Ян Уиттен: Поиск данных. Практическое машинное обучение. Инструменты и методы
ISBN: 9780123748560
Издательство: Elsevier Science
Классификация:
ISBN-10: 0123748569
Обложка/Формат: Paperback
Страницы: 664
Вес: 0.97 кг.
Дата издания: 03.02.2011
Серия: The morgan kaufmann series in data management systems
Язык: English
Издание: 3 rev ed
Иллюстрации: Approx. 120 illustrations; illustrations, unspecified
Размер: 235 mm X 191 mm
Читательская аудитория: Professional & vocational
Подзаголовок: Practical machine learning tools and techniques
Ссылка на Издательство: Link
Рейтинг:
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, youll 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>


      Новое издание
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
Цена: 10034 р.
Наличие на складе: Есть у поставщикаПоставка под заказ.
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


Practical Machine Learning with H2O

Автор: Darren Cook
Название: Practical Machine Learning with H2O
ISBN: 149196460X ISBN-13(EAN): 9781491964606
Издательство: Wiley
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Цена: 6862 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.

Machine Learning and Data Mining in Pattern Recognition

Автор: Petra Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3642030696 ISBN-13(EAN): 9783642030697
Издательство: Springer
Рейтинг:
Цена: 19897 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 6th International Conference MLDM 2009 Leipzig Germany July 2325 2009 Proceedings. .

Data Mining

Автор: Roiger
Название: Data Mining
ISBN: 1498763979 ISBN-13(EAN): 9781498763974
Издательство: Taylor&Francis
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Цена: 9908 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This textbook provides a tutorial-based introduction to data mining with a focus on model building and testing, as well as on interpreting and validating results. The book follows the format of the first edition, but with updates and additions throughout.

Machine Learning and Data Mining in Pattern Recognition

Автор: Perner
Название: Machine Learning and Data Mining in Pattern Recognition
ISBN: 3319419196 ISBN-13(EAN): 9783319419190
Издательство: Springer
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Цена: 14694 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.

Data Mining: Concepts and Techniques,

Автор: Jiawei Han
Название: Data Mining: Concepts and Techniques,
ISBN: 0123814790 ISBN-13(EAN): 9780123814791
Издательство: Elsevier Science
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Цена: 10645 р.
Наличие на складе: Нет в наличии.

Описание: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

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: 9279 р.
Наличие на складе: Нет в наличии.

Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Bayesian Reasoning and Machine Learning

Автор: Barber
Название: Bayesian Reasoning and Machine Learning
ISBN: 0521518148 ISBN-13(EAN): 9780521518147
Издательство: Cambridge Academ
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Цена: 11495 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.

Principles and Theory for Data Mining and Machine Learning

Автор: Clarke
Название: Principles and Theory for Data Mining and Machine Learning
ISBN: 0387981349 ISBN-13(EAN): 9780387981345
Издательство: Springer
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Цена: 30611 р.
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Описание: Extensive treatment of the most up-to-date topicsProvides the theory and concepts behind popular and emerging methodsRange of topics drawn from Statistics, Computer Science, and Electrical Engineering


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