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Managing and Mining Sensor Data, Charu C. Aggarwal


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Цена: 13974.00р.
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Автор: Charu C. Aggarwal
Название:  Managing and Mining Sensor Data
ISBN: 9781461463085
Издательство: Springer
Классификация:



ISBN-10: 1461463084
Обложка/Формат: Hardcover
Страницы: 534
Вес: 0.88 кг.
Дата издания: 15.01.2013
Язык: English
Размер: 241 x 162 x 34
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process.


Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking

Автор: Foster Provost
Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking
ISBN: 1449361323 ISBN-13(EAN): 9781449361327
Издательство: Wiley
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Цена: 6334.00 р.
Наличие на складе: Есть (1 шт.)
Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.

Data Mining and Big Data

Автор: Tan
Название: Data Mining and Big Data
ISBN: 3319409727 ISBN-13(EAN): 9783319409726
Издательство: Springer
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Цена: 11179.00 р.
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Описание: The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions.

Trends and Applications in Knowledge Discovery and Data Mining

Автор: Cao
Название: Trends and Applications in Knowledge Discovery and Data Mining
ISBN: 3319429957 ISBN-13(EAN): 9783319429953
Издательство: Springer
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Цена: 6988.00 р.
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Описание: This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2016, held in conjunction with PAKDD, the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented were carefully reviewed and selected from 38 submissions.

Data Mining: Foundations and Intelligent Paradigms

Автор: Dawn E. Holmes; Lakhmi C. Jain
Название: Data Mining: Foundations and Intelligent Paradigms
ISBN: 3642435467 ISBN-13(EAN): 9783642435461
Издательство: Springer
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Цена: 29209.00 р.
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Описание: This volume, which includes the latest research on data mining and its applications to financial modeling, presents its material in an easy-to-consult handbook style and is aimed at a broad audience that includes both specialists and non-specialists alike.

Data Mining In Dynamic Social Networks And Fuzzy Systems

Автор: Bhatnagar
Название: Data Mining In Dynamic Social Networks And Fuzzy Systems
ISBN: 1466642130 ISBN-13(EAN): 9781466642133
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: <em>Data Mining in Dynamic Social Networks and Fuzzy Systems</em> brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organisational development.

Managing and Mining Sensor Data

Автор: Charu C. Aggarwal
Название: Managing and Mining Sensor Data
ISBN: 1489992383 ISBN-13(EAN): 9781489992383
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process.

Data Mining: The Textbook

Автор: С.Aggarwal
Название: Data Mining: The Textbook
ISBN: 3319141414 ISBN-13(EAN): 9783319141411
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.

Managing and Mining Graph Data

Автор: Charu C. Aggarwal; Haixun Wang
Название: Managing and Mining Graph Data
ISBN: 1461425603 ISBN-13(EAN): 9781461425601
Издательство: Springer
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Цена: 27251.00 р.
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Описание: Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy.

Managing and Mining Uncertain Data

Автор: Charu C. Aggarwal
Название: Managing and Mining Uncertain Data
ISBN: 1441935177 ISBN-13(EAN): 9781441935175
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This collection of surveys presents the most recent models, algorithms and applications in mining uncertain data. Organized to make it more accessible to applications-driven practitioners, it includes case studies based on real-world examples.

Managing and Mining Graph Data

Автор: Charu C. Aggarwal; Haixun Wang
Название: Managing and Mining Graph Data
ISBN: 1441960449 ISBN-13(EAN): 9781441960443
Издательство: Springer
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Цена: 25155.00 р.
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Описание: Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy.

Data Mining Techniques in Sensor Networks

Автор: Annalisa Appice; Anna Ciampi; Fabio Fumarola; Dona
Название: Data Mining Techniques in Sensor Networks
ISBN: 1447154533 ISBN-13(EAN): 9781447154532
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Sensor networks comprise of a number of sensors installed across a spatially distributed network, which gather information and periodically feed a central server with the measured data. One solution is to compute summaries of the data as it arrives, and to use these summaries to interpolate the real data.

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.
Наличие на складе: Нет в наличии.

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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