Data mining concepts and techniques

Browse book content About the book Search in this book. Browse content Table of contents. 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. The style of the book is rigorous and detailed but readable and engaging.

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The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data.

Data Mining: Concepts and Techniques,

The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. Mjning Concepts and Methods Publisher Summary Concepts and Techniques, 3rd Edition 2 reviews.

Approved centre forum ACF. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Micheline Kamber Simon Fraser University.

Data mining is a relatively young field in computing, which broadly aims to provide tools and techniques to assist in the integration of disparate data sets and in the discovery of hidden patterns and relationships in these data sets. Mining Frequent Patterns, Associations, and Correlations: Search in this book. Choose your membership Continue an application. Data Cube Technology Publisher Summary 5.

A broad range of topics are covered, from an initial overview of the field of data mining and its fundamental concepts, to data preparation, data warehousing, OLAP, pattern discovery and data classification. Also in this section Academic accreditation.

Bibliographical notes at the end of each chapter provide a brief but informative guide to the related literature and the book contains extensive references. 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.

This book eata intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. A Road Map 7.

anx After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. With Safari, you learn the way you learn best. Find out more by reading our cookies policy. Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Concepts and Techniques provides the concepts and techniques in processing gathered data or minibg, which will be used in various applications.

It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets.

Our website uses cookies to help improve your experience. Whereas the original rationale for such data collection may have been for legal reasons, billing, traditional reporting and analysis applications and so forth, data owners have become increasingly interested in deriving additional value from their data.

Advanced Methods Publisher Summary 9. Start Free Trial No credit card required.

Han and Kamber: Data MiningConcepts and Techniques, 2nd ed., Morgan Kaufmann,

By continuing you agree to the use of cookies. Introduction Publisher Summary 1. The extensive use of computers in many commercial and research applications has enabled the collection of large amounts of data.

Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. Outlier Detection Publisher Summary Advanced Pattern Mining Publisher Summary 7.

The style of the book is rigorous and detailed but readable and engaging. This book is referred minign the knowledge discovery from data KDD.

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