Data mining and data warehousing : (Record no. 91935)

MARC details
000 -LEADER
fixed length control field 02495nam a2200325Ia 4500
001 - CONTROL NUMBER
control field 355640
003 - CONTROL NUMBER IDENTIFIER
control field 0000000000
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20211104093422.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190403t20192019enka b 001 0 eng c
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2019013358
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108727747;1108727743
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1055456089
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1055456089
040 ## - CATALOGING SOURCE
Original cataloging agency LBSOR/DLC
Transcribing agency DLC
Description conventions rda
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA 76.9.D343
Item number .B469 2019
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Bhatia, Parteek,
9 (RLIN) 128258
245 #0 - TITLE STATEMENT
Title Data mining and data warehousing :
Remainder of title principles and practical techniques /
Statement of responsibility, etc. Parteek Bhatia
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cambridge, United Kingdom ;;New York, NY :
Name of producer, publisher, distributor, manufacturer Cambridge University Press,
Date of production, publication, distribution, manufacture, or copyright notice c2019.
300 ## - PHYSICAL DESCRIPTION
Extent xxiv, 477 pages
Dimensions 24 cm.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Beginning with machine learning -- Introduction to data mining -- Beginning with Weka and R language -- Data preprocessing -- Classification -- Implementing classification in Weka and R -- Cluster analysis -- Implementing clustering with Weka and R -- Association mining -- Implementing association mining with Weka and R -- Web mining and search engines -- Data warehouse -- Data warehouse schema -- Online analytical processing -- Big data and NoSQL
520 ## - SUMMARY, ETC.
Summary, etc. This 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. It brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Na©¯ve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. 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. Unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding--
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining
9 (RLIN) 23723
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data warehousing
9 (RLIN) 70604
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type

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