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Foundations and Novel Approaches in Data Mining, Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi


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Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi
Название:  Foundations and Novel Approaches in Data Mining
ISBN: 9783642066504
Издательство: Springer
Классификация:


ISBN-10: 364206650X
Обложка/Формат: Paperback
Страницы: 386
Вес: 0.59 кг.
Дата издания: 2005
Серия: Studies in Computational Intelligence
Язык: English
Издание: 1st ed. softcover of
Иллюстрации: 56 black & white tables, biography
Размер: 234 x 156 x 20
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
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.

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: 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.

Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 61750.00 T
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Описание:

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
  • Includes open-access online courses that introduce practical applications of the material in the book

Data Mining: Foundations and Intelligent Paradigms

Автор: Dawn E. Holmes; Lakhmi C. Jain
Название: Data Mining: Foundations and Intelligent Paradigms
ISBN: 3642430937 ISBN-13(EAN): 9783642430930
Издательство: Springer
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Цена: 156720.00 T
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Описание: However, in compiling a volume titled "DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification" we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

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: 64800.00 T
Наличие на складе: Поставка под заказ.
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: 57970.00 T
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>

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: 60220.00 T
Наличие на складе: Поставка под заказ.
Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

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: 180180.00 T
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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 with R

Автор: Torgo
Название: Data Mining with R
ISBN: 1439810184 ISBN-13(EAN): 9781439810187
Издательство: Taylor&Francis
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Цена: 66340.00 T
Наличие на складе: Поставка под заказ.
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.

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: 204040.00 T
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Описание: Presents a theoretical foundation of data-mining and provides important directions for data-mining research.

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: 65210.00 T
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.

Foundations and Advances in Data Mining

Автор: Wesley Chu; Tsau Young Lin
Название: Foundations and Advances in Data Mining
ISBN: 3642425380 ISBN-13(EAN): 9783642425387
Издательство: Springer
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Цена: 181670.00 T
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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.

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: 181670.00 T
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.


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