Paramètres
- 744pages
- 27 heures de lecture
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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.
Achat du livre
Data Mining, Jiawei Han, Micheline Kamber, Jian Pei
- Langue
- Année de publication
- 2011
- product-detail.submit-box.info.binding
- (rigide)
Modes de paiement
Il manque plus que ton avis ici.
- Titre
- Data Mining
- Sous-titre
- Concepts and Techniques - Third Edition
- Langue
- Anglais
- Auteurs
- Jiawei Han, Micheline Kamber, Jian Pei
- Éditeur
- Morgan Kaufmann Publishers
- Publié
- 2011
- Format
- rigide
- Pages
- 744
- ISBN10
- 0123814790
- ISBN13
- 9780123814791
- Séries
- Mots clés
- Nonfiction, Manuels, Technologie & Ingénierie, Manuels et guides, Informatique & Internet, Technologie
- Évaluation
- 3,8 sur 5
- Description
- 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.