Data Mining: Foundations and Practice, Tsau Young Lin; Ying Xie; Anita Wasilewska; Churn-
Автор: Witten, Ian H. Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed. ISBN: 0128042915 ISBN-13(EAN): 9780128042915 Издательство: Elsevier Science Рейтинг: Цена: 61750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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
Автор: С.Aggarwal Название: Data Mining: The Textbook ISBN: 3319141414 ISBN-13(EAN): 9783319141411 Издательство: Springer Рейтинг: 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.
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: 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.
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: 204040.00 T 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: Dawn E. Holmes; Lakhmi C. Jain Название: Data Mining: Foundations and Intelligent Paradigms ISBN: 3642434290 ISBN-13(EAN): 9783642434297 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data mining is a rapidly growing research area in computer science and statistics. Volume 2 of this three-volume series covers theoretical aspects of the subject, including statistical, Bayesian, time-series and others relevant to health informatics.
Автор: Walter W. Piegorsch Название: Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery ISBN: 111903065X ISBN-13(EAN): 9781119030652 Издательство: Wiley Рейтинг: Цена: 17900.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery.
Автор: Ratner Bruce Название: Statistical and Machine-Learning Data Mining ISBN: 1439860912 ISBN-13(EAN): 9781439860915 Издательство: Taylor&Francis Рейтинг: Цена: 60220.00 T Наличие на складе: Нет в наличии. Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.
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 Рейтинг: Цена: 204040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents a theoretical foundation of data-mining and provides important directions for data-mining research.
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.
Автор: Dawn E. Holmes; Lakhmi C. Jain Название: Data Mining: Foundations and Intelligent Paradigms ISBN: 3642430937 ISBN-13(EAN): 9783642430930 Издательство: Springer Рейтинг: Цена: 156720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Dawn E. Holmes; Lakhmi C. Jain Название: Data Mining: Foundations and Intelligent Paradigms ISBN: 3642435467 ISBN-13(EAN): 9783642435461 Издательство: Springer Рейтинг: Цена: 194730.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume, which includes the latest research on data mining and its applications to financial modeling, presents its material in an easy-to-consult handbook style and is aimed at a broad audience that includes both specialists and non-specialists alike.
Автор: Jiawei Han Название: Data Mining: Concepts and Techniques, ISBN: 0123814790 ISBN-13(EAN): 9780123814791 Издательство: Elsevier Science Рейтинг: 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.
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