| Title : | Introduction to data mining |
| Material Type: | printed text |
| Authors: | Pang-Ning Tan, Author ; V. Kumar, Author ; Michael Steinbach, Author ; Anuj Karpatne, Author |
| Publisher: | New York : Pearson Education |
| Publication Date: | 2019 |
| Pagination: | xix, 839 p. |
| Layout: | ill. |
| Size: | 24 cm |
| ISBN (or other code): | 978-0-13-312890-1 |
| General note: | Includes bibliographic references (p. 806-808)
Includes indexes (p. 816-838) |
| Languages : | English (eng) Original Language : English (eng) |
| Descriptors: | Data mining
Database management
Knowledge acquisition (Expert systems)
|
| Class number: | 006.312 |
| Abstract: | Introduction to Data Mining - gives a comprehensive overview of the background and general themes of data mining and is designed to be useful to students, instructors, researchers, and professionals. Presented in a clear and accessible way, the book outlines fundamental concepts and algorithms for each topic, thus providing the reader with the necessary background for the application of data mining to real problems. The text helps readers understand the nuances of the subject, and includes important sections on classification, association analysis, and cluster analysis. This edition improves on the first iteration of the book, published over a decade ago, by addressing the significant changes in the industry as a result of advanced technology and data growth. |
| Contents note: | Introduction; Data; Classification : basic concepts and techniques; Classification : alternative techniques; Association analysis : basic concepts and algorithms; Association analysis : advanced concepts; Cluster analysis : basic concepts and algorithms; Cluster analysis : additional issues and algorithms; Anomaly detection; Avoiding false discoveries; |
| Record link: | https://library.seeu.edu.mk/index.php?lvl=notice_display&id=22088 |
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