Автор: Wesley W. Chu Название: Data Mining and Knowledge Discovery for Big Data ISBN: 3662509458 ISBN-13(EAN): 9783662509456 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book address topics ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.
Автор: Chu Wesley W. Название: Data Mining and Knowledge Discovery for Big Data ISBN: 3642408362 ISBN-13(EAN): 9783642408366 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book address topics ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.
Автор: Wei Wang; Jiong Yang Название: Mining Sequential Patterns from Large Data Sets ISBN: 1441937072 ISBN-13(EAN): 9781441937070 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: С.Aggarwal Название: Data Mining: The Textbook ISBN: 3319141414 ISBN-13(EAN): 9783319141411 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Поставка под заказ.
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.
Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi Название: Foundations and Novel Approaches in Data Mining ISBN: 364206650X ISBN-13(EAN): 9783642066504 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research.
Автор: Cerquitelli, Tania, Quercia, Daniele, Pasquale, Frank (Eds.) Название: Transparent data mining for big and small data. ISBN: 3319540238 ISBN-13(EAN): 9783319540238 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.
Автор: Lars Eld?n Название: Matrix Methods in Data Mining and Pattern Recognition ISBN: 0898716268 ISBN-13(EAN): 9780898716269 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. 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: 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 Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.
Автор: Dominik Slezak; JingTao Yao; James F. Peters; Wojc Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing ISBN: 3540286608 ISBN-13(EAN): 9783540286608 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains papers from the proceedings of the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, held in Regina, Canada in August/September 2005 in 2 volumes.
Автор: Da Ruan; Guoqing Chen; Etienne E. Kerre; Geert Wet Название: Intelligent Data Mining ISBN: 3642065767 ISBN-13(EAN): 9783642065767 Издательство: Springer Рейтинг: Цена: 36570.00 р. 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: Sameer Singh; Maneesha Singh; Chid Apte; Petra Per Название: Pattern Recognition and Data Mining ISBN: 3540287574 ISBN-13(EAN): 9783540287575 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the Third International Conference on Advances in Pattern Recognition, ICAPR 2005, held in Bath, UK in August 2005.
Автор: Dominik Slezak; Marcin Szczuka; Ivo Duentsch; Yiyu Название: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing ISBN: 3540286535 ISBN-13(EAN): 9783540286530 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part of a two volume set, this title includes information related to rough set approximations, rough-algebraic foundations, feature selection and reduction, rough-probabilistic approaches, rough-fuzzy hybridization, fuzzy methods in data analysis, evolutionary computing, machine learning, probabilistic network models, granular computing, and more.
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