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...
Gespeichert in:
| Beteilige Person: | |
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| Weitere beteiligte Personen: | , |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Waltham, MA
Morgan Kaufmann/Elsevier
2012
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| Ausgabe: | 3rd ed. |
| Schriftenreihe: | Morgan Kaufmann series in data management systems
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| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9780123814791/?ar |
| Zusammenfassung: | 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. |
| Beschreibung: | Includes bibliographical references (pages 633-671) and index. - Print version record |
| Umfang: | 1 Online-Ressource (xxxv, 703 Seiten) illustrations, facsimiles. |
| ISBN: | 0123814790 9780123814791 9780123814807 0123814804 1283171171 9781283171175 9786613171177 6613171174 |
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| language | English |
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| spelling | Han, Jiawei VerfasserIn aut Data mining concepts and techniques Jiawei Han, Micheline Kamber, Jian Pei 3rd ed. Waltham, MA Morgan Kaufmann/Elsevier 2012 1 Online-Ressource (xxxv, 703 Seiten) illustrations, facsimiles. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Morgan Kaufmann series in data management systems Includes bibliographical references (pages 633-671) and index. - Print version record 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. English. Data mining Exploration de données (Informatique) Kamber, Micheline MitwirkendeR ctb Pei, Jian MitwirkendeR ctb 9780123814791 Erscheint auch als Druck-Ausgabe 9780123814791 |
| spellingShingle | Han, Jiawei Data mining concepts and techniques Data mining Exploration de données (Informatique) |
| title | Data mining concepts and techniques |
| title_auth | Data mining concepts and techniques |
| title_exact_search | Data mining concepts and techniques |
| title_full | Data mining concepts and techniques Jiawei Han, Micheline Kamber, Jian Pei |
| title_fullStr | Data mining concepts and techniques Jiawei Han, Micheline Kamber, Jian Pei |
| title_full_unstemmed | Data mining concepts and techniques Jiawei Han, Micheline Kamber, Jian Pei |
| title_short | Data mining |
| title_sort | data mining concepts and techniques |
| title_sub | concepts and techniques |
| topic | Data mining Exploration de données (Informatique) |
| topic_facet | Data mining Exploration de données (Informatique) |
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