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Data Mining: Introductory and Advanced Topics by Dunham, Margaret H.
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Parametry przedmiotu
- Stan
- Book Title
- Data Mining: Introductory and Advanced Topics
- ISBN
- 9780130888921
- Subject Area
- Computers
- Publication Name
- Data Mining: Introductory and Advanced Topics
- Publisher
- Prentice Hall PTR
- Item Length
- 9 in
- Subject
- Databases / Data Warehousing, Databases / Data Mining
- Publication Year
- 2002
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Height
- 0.8 in
- Item Weight
- 18.7 Oz
- Item Width
- 7 in
- Number of Pages
- 336 Pages
O tym produkcie
Product Identifiers
Publisher
Prentice Hall PTR
ISBN-10
0130888923
ISBN-13
9780130888921
eBay Product ID (ePID)
2242639
Product Key Features
Number of Pages
336 Pages
Publication Name
Data Mining: Introductory and Advanced Topics
Language
English
Publication Year
2002
Subject
Databases / Data Warehousing, Databases / Data Mining
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
0.8 in
Item Weight
18.7 Oz
Item Length
9 in
Item Width
7 in
Additional Product Features
Intended Audience
College Audience
LCCN
2002-075976
Dewey Edition
21
Reviews
"It is the best book on data mining so far, and I would definitely adopt it for my course. The book is very comprehensive and covers all of the data mining topics and algorithms of which 1 am aware. The depth of coverage of each topic or method is exactly right and appropriate. Each algorithm is presented in pseudocode that is sufficient for any interested readers to convert into a working implementation in a computer language of their choice." Michael H. Huhns, University of South Carolina "Discussion on distributed, parallel, and incremental algorithms is outstanding." Zoran Obradovic, Temple University, "It is the best book on data mining so far, and I would definitely adopt it for my course. The book is very comprehensive and covers all of the data mining topics and algorithms of which 1 am aware. The depth of coverage of each topic or method is exactly right and appropriate. Each algorithm is presented in pseudocode that is sufficient for any interested readers to convert into a working implementation in a computer language of their choice." -- Michael H. Huhns, University of South Carolina "Discussion on distributed, parallel, and incremental algorithms is outstanding." -- Zoran Obradovic, Temple University, "It is the best book on data mining so far, and I would definitely adopt it for my course. The book is very comprehensive and covers all of the data mining topics and algorithms of which 1 am aware. The depth of coverage of each topic or method is exactly right and appropriate. Each algorithm is presented in pseudocode that is sufficient for any interested readers to convert into a working implementation in a computer language of their choice." — Michael H. Huhns, University of South Carolina "Discussion on distributed, parallel, and incremental algorithms is outstanding." — Zoran Obradovic, Temple University, " It is the best book on data mining so far, and I would definitely adopt it for my course. The book is very comprehensive and covers all of the data mining topics and algorithms of which 1 am aware. The depth of coverage of each topic or method is exactly right and appropriate. Each algorithm is presented in pseudocode that is sufficient for any interested readers to convert into a working implementation in a computer language of their choice. " — Michael H. Huhns,University of South Carolina " Discussion on distributed, parallel, and incremental algorithms is outstanding. " — Zoran Obradovic,Temple University
Illustrated
Yes
Dewey Decimal
006.3
Table Of Content
I. INTRODUCTION. 1. Introduction. 2. Related Concepts. 3. Data Mining Techniques. II. CORE TOPICS. 4. Classification. 5. Clustering. 6. Association Rules. III. ADVANCED TOPICS. 7. Web Mining. 8. Spatial Mining. 9. Temporal Mining. IV. APPENDIX. 10. Data Mining Products.
Synopsis
For courses in data mining. Thorough in its coverage from basic to advanced topics, this text presents the algorithms and techniques used in data mining. It introduces readers to various data mining concepts and algorithms., Thorough in its coverage from basic to advanced topics, this book presents the key algorithms and techniques used in data mining. An emphasis is placed on the use of data mining concepts in real world applications with large database components. Includes unique chapters on Web mining, spatial mining, temporal mining, and prototypes and DM products. Separate case studies section highlights real world applications., Thorough in its coverage from basic to advanced topics, this book presents the key algorithms and techniques used in data mining. An emphasis is placed on the use of data mining concepts in real world applications with large database components. Includes unique chapters on Web mining, spatial mining, temporal mining, and prototypes and DM products. Separate case studies section highlights real world applications. An excellent reference book for computer database professionals and researchers.
LC Classification Number
QA76.9.D343D86 2002
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