Mastering Data Mining (Record no. 31969)

MARC details
000 -LEADER
fixed length control field 01235nam a2200205Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190122144058.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140910s9999 xx 000 0 und d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788126518258
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Item number BER - M
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Berry,Michael J.A.
245 ## - TITLE STATEMENT
Title Mastering Data Mining
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Delhi
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc John Wily
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Date of publication, distribution, etc 2000
300 ## - PHYSICAL DESCRIPTION
Extent 494p
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element IT & CS
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="Part I: Setting The Focus Data Mining in Context Why Master the Art? Data Mining Methodology: The Virtuous Cycle Revisited Customers and Their Lifecycles Part II: The Three Pillars Of Data Mining Data Mining Techniques and Algorithms Data, Data Everywhere... Building Effective Predictive Models Taking Control: Setting Up a Data Mining Environment Part III: Case Studies Who Needs Bag Balm and Pants Stretchers Who Gets What? Building a Best Next Offer Model for an Online Bank Please Don't Go! Churn Modeling in Wireless Communication Converging on the Customer: Understanding Customer Behavior in the Telecommunications Industry Who Is Buying What? Getting to Know Supermarket Shoppers Waste Not, Want Not: Improving Manufacturing Processes. The Societal Context: Data Mining and Privacy">Part I: Setting The Focus Data Mining in Context Why Master the Art? Data Mining Methodology: The Virtuous Cycle Revisited Customers and Their Lifecycles Part II: The Three Pillars Of Data Mining Data Mining Techniques and Algorithms Data, Data Everywhere... Building Effective Predictive Models Taking Control: Setting Up a Data Mining Environment Part III: Case Studies Who Needs Bag Balm and Pants Stretchers Who Gets What? Building a Best Next Offer Model for an Online Bank Please Don't Go! Churn Modeling in Wireless Communication Converging on the Customer: Understanding Customer Behavior in the Telecommunications Industry Who Is Buying What? Getting to Know Supermarket Shoppers Waste Not, Want Not: Improving Manufacturing Processes. The Societal Context: Data Mining and Privacy</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Inventory number Total Checkouts Full call number Barcode Date last seen Uniform Resource Identifier Price effective from Koha item type
    Dewey Decimal Classification   Not For Loan Reference Amity Central Library Amity Central Library ASET M.Tech CSE 03/02/2018 SBA 2495.00 SBA / 12050 22/12/2017   005.74 BER - M 26253 22/01/2019 005.74 BER-M 03/02/2018 Reference Book
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