Domain Driven Data Mining, Longbing Cao; Philip S. Yu; Chengqi Zhang; Yanchan
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 Рейтинг: Цена: 42230.00 T Наличие на складе: Есть 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.
Автор: Brown Meta S. Название: Data Mining for Dummies ISBN: 1118893174 ISBN-13(EAN): 9781118893173 Издательство: Wiley Рейтинг: Цена: 33780.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum.
Автор: Lars Eld?n Название: Matrix Methods in Data Mining and Pattern Recognition ISBN: 0898716268 ISBN-13(EAN): 9780898716269 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Поставка под заказ. Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.
Автор: Djamel A. Zighed; Shusaku Tsumoto; Zbigniew W. Ras Название: Mining Complex Data ISBN: 3642099807 ISBN-13(EAN): 9783642099809 Издательство: Springer Рейтинг: Цена: 194730.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g.
Название: Data Mining and Applications in Genomics ISBN: 1402089740 ISBN-13(EAN): 9781402089749 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Charu C. Aggarwal; Philip S. Yu Название: Privacy-Preserving Data Mining ISBN: 1441943714 ISBN-13(EAN): 9781441943712 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book proposes a number of techniques to perform data mining tasks in a privacy-preserving way. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively.
Автор: Zbigniew W. Ras; Shusaku Tsumoto; Djamel A. Zighed Название: Mining Complex Data ISBN: 3540684158 ISBN-13(EAN): 9783540684152 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007.
Автор: Wei Wang; Jiong Yang Название: Mining Sequential Patterns from Large Data Sets ISBN: 1441937072 ISBN-13(EAN): 9781441937070 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Related Work.- Periodic Patterns.- Statistically Significant Patterns.- Approximate Patterns.- Conclusion Remark.
Автор: Takashi Washio; Einoshin Suzuki; Kai Ming Ting; Ak Название: Advances in Knowledge Discovery and Data Mining ISBN: 3540681248 ISBN-13(EAN): 9783540681243 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 12th Pacific-Asia Conference PAKDD 2008 Osaka Japan May 20-23 2008 Proceedings.
Автор: Evangelos Triantaphyllou; Giovanni Felici Название: Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques ISBN: 1441941738 ISBN-13(EAN): 9781441941732 Издательство: Springer Рейтинг: Цена: 222670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications.
Автор: Da Ruan; Guoqing Chen; Etienne E. Kerre; Geert Wet Название: Intelligent Data Mining ISBN: 3642065767 ISBN-13(EAN): 9783642065767 Издательство: Springer Рейтинг: Цена: 243800.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: "Intelligent Data Mining - Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications.
Автор: Wesley Chu; Tsau Young Lin Название: Foundations and Advances in Data Mining ISBN: 3642425380 ISBN-13(EAN): 9783642425387 Издательство: Springer Рейтинг: Цена: 181670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
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