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Data Mining and Big Data, Ying Tan; Hideyuki Takagi; Yuhui Shi


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Цена: 11179.00р.
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Автор: Ying Tan; Hideyuki Takagi; Yuhui Shi
Название:  Data Mining and Big Data
ISBN: 9783319618449
Издательство: Springer
Классификация:





ISBN-10: 331961844X
Обложка/Формат: Paperback
Страницы: 546
Вес: 0.78 кг.
Дата издания: 26.06.2017
Серия: Information Systems and Applications, incl. Internet/Web, and HCI
Язык: English
Издание: 1st ed. 2017
Иллюстрации: 210 illustrations, black and white; xv, 546 p. 210 illus.
Размер: 234 x 156 x 29
Читательская аудитория: Professional & vocational
Основная тема: Computer Science
Подзаголовок: Second International Conference, DMBD 2017, Fukuoka, Japan, July 27 – August 1, 2017, Proceedings
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. They were organized in topical sections named: association analysis; big data; data analysis; data mining;


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.

Developing Churn Models Using Data Mining Techniques And Social Network Analysis

Автор: Klepac, Kopal & Mrsic
Название: Developing Churn Models Using Data Mining Techniques And Social Network Analysis
ISBN: 1466662883 ISBN-13(EAN): 9781466662889
Издательство: Mare Nostrum (Eurospan)
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Цена: 27027.00 р.
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Описание: Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios.Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.

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.

Data Mining and Knowledge Discovery for Big Data

Автор: Wesley W. Chu
Название: Data Mining and Knowledge Discovery for Big Data
ISBN: 3662509458 ISBN-13(EAN): 9783662509456
Издательство: Springer
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Цена: 18284.00 р.
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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.

Data Mining for Dummies

Автор: Brown Meta S.
Название: Data Mining for Dummies
ISBN: 1118893174 ISBN-13(EAN): 9781118893173
Издательство: Wiley
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Цена: 5067.00 р.
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Описание: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum.

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.
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.

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.

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>

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: 9033.00 р.
Наличие на складе: Нет в наличии.

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

Data Mining and Knowledge Discovery for Big Data

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.
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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.

Transparent data mining for big and small data.

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
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Цена: 16769.00 р.
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Описание: This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.

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.
Наличие на складе: Нет в наличии.

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.


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