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Developing Churn Models Using Data Mining Techniques And Social Network Analysis, Klepac, Kopal & Mrsic


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Цена: 21186р.
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Склад Англия: 59 шт.  Склад Америка: 57 шт.  
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Автор: Klepac, Kopal & Mrsic
Название:  Developing Churn Models Using Data Mining Techniques And Social Network Analysis   (Модель оттока внимания с учетом анализа социальных сетей и методов интеллектуального анализа данных)
Издательство: Eurospan
Классификация:
ISBN: 1466662883
ISBN-13(EAN): 9781466662889
ISBN: 1-466-66288-3
ISBN-13(EAN): 978-1-466-66288-9
Обложка/Формат: Hardback
Страницы: 361
Вес: 0.796 кг.
Дата издания: 30.09.2014
Серия: Research essentials collection
Язык: ENG
Иллюстрации: Black & white illustrations
Размер: 25.40 x 17.78 x 1.91 cm
Читательская аудитория: Professional and scholarly
Ключевые слова: Data mining
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Поставляется из: Англии
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: 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: 5343 р. 5937.00 -10%
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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: 4965 р. 5517.00 -10%
Наличие на складе: Поставка под заказ.

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>

Data Mining Techniques in CRM

Автор: Tsiptsis Konstantinos
Название: Data Mining Techniques in CRM
ISBN: 0470743972 ISBN-13(EAN): 9780470743973
Издательство: Wiley
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Цена: 6505 р.
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Описание: This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining.

Foundations and Novel Approaches in Data Mining

Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi
Название: Foundations and Novel Approaches in Data Mining
ISBN: 3540283153 ISBN-13(EAN): 9783540283157
Издательство: Springer
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Цена: 20477 р.
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Описание: Presents a theoretical foundation of data-mining and provides important directions for data-mining research.

Foundations of Data Mining and Knowledge Discovery

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
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Цена: 18232 р.
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Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.

Foundations and Novel Approaches in Data Mining

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
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Цена: 20477 р.
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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.

Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection

Автор: Baesens Bart, Verbeke Wouter, Van Vlasselaer Veron
Название: Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
ISBN: 1119133122 ISBN-13(EAN): 9781119133124
Издательство: Wiley
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Цена: 3970 р.
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Описание: THE DEFINITIVE GUIDE TO THE DETECTION AND PREVENTION OF FRAUD THROUGH DATA ANALYTICS Catch fraud early! Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques shows you how with a thorough overview of how to prevent losses and recov

Social Media Mining And Social Network Analysis

Автор: Xu & Li
Название: Social Media Mining And Social Network Analysis
ISBN: 1466628065 ISBN-13(EAN): 9781466628069
Издательство: Eurospan
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Цена: 19991 р.
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Описание: The widespread use of web-based communities, social media, and social networking sites has brought a rapid change to the interaction between computers and users as well as the digital experience as a whole. &lt;br&gt;&lt;br&gt;&lt;em&gt;Social Media Mining and Social Network Analysis: Emerging Research&lt;/em&gt; highlights the advancements made in social network analysis and social web mining and its influence in the fields of computer science, information systems, sociology, organisation science discipline and much more. This collection of perspectives on developmental practice is useful for industrial practitioners as well as researchers and scholars.

The Influence of Technology on Social Network Analysis and Mining

Автор: ?zyer
Название: The Influence of Technology on Social Network Analysis and Mining
ISBN: 3709113458 ISBN-13(EAN): 9783709113455
Издательство: Springer
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Цена: 13557 р.
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Описание: In recent years, social network research has advanced significantly with the development of sophisticated techniques for Social Network Analysis and Mining (SNAM). This book traces parallels between new social media and similar social patterns.

Advances in Social Network Mining and Analysis

Автор: Giles
Название: Advances in Social Network Mining and Analysis
ISBN: 3642149286 ISBN-13(EAN): 9783642149283
Издательство: Springer
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Цена: 5609 р.
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Описание: This year`s volume of Advances in Social Network Analysis contains the p- ceedings for the Second International Workshop on Social Network Analysis (SNAKDD 2008).

Social Network Analysis in Predictive Policing

Автор: Tayebi
Название: Social Network Analysis in Predictive Policing
ISBN: 3319414917 ISBN-13(EAN): 9783319414911
Издательство: Springer
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Цена: 7199 р.
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Описание:

This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks—networks of offenders who have committed crimes together—have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-offending network analysis as effective tool for predictive policing. The formal representation of criminological concepts presented here allow computer scientists to think about algorithmic and computational solutions to problems long discussed in the criminology literature. For each of the studied problems, we start with well-founded concepts and theories in criminology, then propose a computational method and finally provide a thorough experimental evaluation, along with a discussion of the results. In this way, the reader will be able to study the complete process of solving real-world multidisciplinary problems.
Data Mining Techniques

Автор: Berry Michael J
Название: Data Mining Techniques
ISBN: 0470650931 ISBN-13(EAN): 9780470650936
Издательство: Wiley
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Цена: 3970 р.
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Описание: The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new editionmore than 50% new and revised is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.  Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more Provides best practices for performing data mining using simple tools such as Excel Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.


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