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Making Sense of Data II - A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications, Myatt


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Автор: Myatt
Название:  Making Sense of Data II - A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications
ISBN: 9780470222805
Издательство: Wiley
Классификация:
ISBN-10: 0470222808
Обложка/Формат: Paperback
Страницы: 308
Вес: 0.42 кг.
Дата издания: 10.03.2009
Язык: English
Иллюстрации: Illustrations
Размер: 233 x 166 x 17
Читательская аудитория: Tertiary education (us: college)
Основная тема: Data Mining Statistics
Подзаголовок: A practical guide to data visualization, advanced data mining methods, and applications
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This book provides a general end-to-end discussion concerning the process of translating raw data to scientific and business decisions. The reader`s ability to find patterns in data will be greatly enhanced due to the book`s combination of statistical learning with powerful visualization techniques.


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: 9720.00 р.
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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.

Advances in Data Mining. Applications and Theoretical Aspects

Автор: Petra Perner
Название: Advances in Data Mining. Applications and Theoretical Aspects
ISBN: 3642030661 ISBN-13(EAN): 9783642030666
Издательство: Springer
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Цена: 12157.00 р.
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Описание: The topics range from theoretical aspects of data mining to app- cations of data mining, such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society.

Advances in Data Mining. Applications and Theoretical Aspects

Автор: Perner
Название: Advances in Data Mining. Applications and Theoretical Aspects
ISBN: 3319415603 ISBN-13(EAN): 9783319415604
Издательство: Springer
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Цена: 10342.00 р.
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Описание: This book constitutes the refereed proceedings of the 16th Industrial Conference on Advances in Data Mining, ICDM 2016, held in New York, NY, USA, in July 2016. The 33 revised full papers presented were carefully reviewed and selected from 100 submissions.

Data Mining with R

Автор: Torgo
Название: Data Mining with R
ISBN: 1439810184 ISBN-13(EAN): 9781439810187
Издательство: Taylor&Francis
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Цена: 9951.00 р.
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Описание: This hands-on book uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, it covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. The main data mining processes and techniques are presented through detailed, real-world case studies. With these case studies, the author supplies all necessary steps, code, and data. Mirroring the do-it-yourself approach of the text, the supporting website provides data sets and R code.

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>

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.

Advanced Data Mining and Applications

Автор: Ronghuai Huang; Qiang Yang; Jian Pei; Jo?o Gama; X
Название: Advanced Data Mining and Applications
ISBN: 3642033474 ISBN-13(EAN): 9783642033476
Издательство: Springer
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Цена: 19564.00 р.
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Описание: 5th International Conference ADMA 2009 Chengdu China August 1719 2009 Proceedings. .

Advanced Data Mining and Applications

Автор: Tang
Название: Advanced Data Mining and Applications
ISBN: 3540881913 ISBN-13(EAN): 9783540881919
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Constitutes the refereed proceedings of the 4th International Conference on Advanced Data Mining and Applications, ADMA 2008, held in Chengdu, China, in October 2008. This book focuses on advancements in data mining and peculiarities and challenges of real world applications using data mining.

Advanced Data Mining and Applications

Автор: Li
Название: Advanced Data Mining and Applications
ISBN: 3319495852 ISBN-13(EAN): 9783319495859
Издательство: Springer
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Цена: 14814.00 р.
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Описание: The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.

Data Mining and Applications in Genomics

Название: Data Mining and Applications in Genomics
ISBN: 1402089740 ISBN-13(EAN): 9781402089749
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford.


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