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Data Mining and Data Warehousing:Principles and Practical Techniques (Record no. 2488)

MARC details
000 -LEADER
fixed length control field 02562nam a22002057a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200224112009.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200118b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 978-1-108-72774-7
028 ## - PUBLISHER NUMBER
Source Allied Informatics, Jaipur
Bill Number 7084
Bill Date 13/01/2020
Purchase Year 2019-20
040 ## - CATALOGING SOURCE
Original cataloging agency BSDU
Language of cataloging English
Transcribing agency BSDU
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number BHA
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bhatia,Parteek
245 ## - TITLE STATEMENT
Title Data Mining and Data Warehousing:Principles and Practical Techniques
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. United Kingdom
Name of publisher, distributor, etc. Cambridge University Press
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent 477
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.<br/><br/>Discusses important concepts with their practical implementation using Weka and R language data mining tools<br/>Includes advanced topics such as big data analytics, relational data models and NoSQL that are discussed in detail<br/>Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding<br/><br/>Preface<br/>Acknowledgement<br/>Dedication<br/>1. Beginning with machine learning<br/>2. Introduction to data mining<br/>3. Beginning with Weka and R language<br/>4. Data pre-processing<br/>5. Classification<br/>6. Implementing classification in Weka and R<br/>7. Cluster analysis<br/>8. Implementing clustering with Weka and R<br/>9. Association mining<br/>10. Implementing association mining with Weka and R<br/>11. Web mining and search engine<br/>12. Operational data store and data warehouse<br/>13. Data warehouse schema<br/>14. Online analytical processing<br/>15. Big data and NoSQL
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data Mining
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     BSDU Knowledge Resource Center, Jaipur BSDU Knowledge Resource Center, Jaipur General Stacks 01/18/2020 695.00   006.312 BHA 018035 02/12/2020 695.00 01/18/2020 Books