Cargando…
Data Mining: Concepts and Techniques.
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 kn...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Elsevier Science
2011.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000M 4500 | ||
|---|---|---|---|
| 001 | KNOVEL_ocn968099315 | ||
| 003 | OCoLC | ||
| 005 | 20231027140348.0 | ||
| 006 | m o d | ||
| 007 | cr ||||||||||| | ||
| 008 | 110609s2011 xx o 000 0 eng d | ||
| 040 | |a FEM |b eng |e pn |c FEM |d OCLCQ |d ESU |d OCLCF | ||
| 019 | |a 969026816 | ||
| 020 | |a 9780123814807 |q (electronic bk.) | ||
| 020 | |a 0123814804 | ||
| 035 | |a (OCoLC)968099315 |z (OCoLC)969026816 | ||
| 050 | 4 | |a QA76.9.D343H36 2011eb | |
| 082 | 0 | 4 | |a 006.3/12 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Han, Jiawei, |e author. | |
| 245 | 1 | 0 | |a Data Mining: Concepts and Techniques. |
| 260 | |b Elsevier Science |c 2011. | ||
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |2 rda | ||
| 520 | |a 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. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data. | ||
| 588 | 0 | |a Vendor-supplied metadata. | |
| 505 | 0 | |a Front Cover; Data Mining: Concepts and Techniques; Copyright; Dedication; Table of Contents; Foreword; Foreword to Second Edition; Preface; Acknowledgments; About the Authors; Chapter 1. Introduction; Chapter 2. Getting to Know Your Data; Chapter 3. Data Preprocessing; Chapter 4. Data Warehousing and Online Analytical Processing; Chapter 5. Data Cube Technology; Chapter 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods; Chapter 7. Advanced Pattern Mining; Chapter 8. Classification: Basic Concepts; Chapter 9. Classification: Advanced Methods. | |
| 505 | 8 | |a Chapter 10. Cluster Analysis: Basic Concepts and MethodsChapter 11. Advanced Cluster Analysis; Chapter 12. Outlier Detection; Chapter 13. Data Mining Trends and Research Frontiers; Bibliography; Index. | |
| 590 | |a Knovel |b ACADEMIC - General Engineering & Project Administration | ||
| 590 | |a Knovel |b ACADEMIC - Software Engineering | ||
| 650 | 0 | |a Data mining. | |
| 650 | 1 | 7 | |a Data mining. |2 bisacsh |
| 650 | 7 | |a Data mining. |2 fast |0 (OCoLC)fst00887946 | |
| 655 | 4 | |a Databases; Artificial Intelligence. | |
| 700 | 1 | |a Jian Pei, |e author. | |
| 700 | 1 | |a Micheline Kamber, |e author. | |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpDMCTE007/toc |z Texto completo |
| 994 | |a 92 |b IZTAP | ||