Microsoft data mining : (Record no. 3727)

MARC details
000 -LEADER
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001 - CONTROL NUMBER
control field 12194515
003 - CONTROL NUMBER IDENTIFIER
control field KE-MeUCS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20050607104252.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 001003s2000 maua 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 00047514
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1555582427 (pbk. : alk. paper)
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Transcribing agency DLC
Modifying agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.D343
Item number D43 2001
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 21
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name De Ville, Barry.
9 (RLIN) 3095
245 10 - TITLE STATEMENT
Title Microsoft data mining :
Remainder of title integrated business intelligence for e-Commerce and knowledge management /
Statement of responsibility, etc Barry de Ville.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Boston :
Name of publisher, distributor, etc Digital Press,
Date of publication, distribution, etc c2001.
300 ## - PHYSICAL DESCRIPTION
Extent xx, 315 :
Other physical details ill. ;
Dimensions 24 cm.
500 ## - GENERAL NOTE
General note Includes index.
505 8# - FORMATTED CONTENTS NOTE
Formatted contents note Machine generated contents note: -- I Introduction to Data Mining -- I.I Something old, something new -- 1.2 Microsoft's approach to developing the right set of tools -- 1.3 Benefits of data mining -- 1.4 Microsoft's entry into data mining -- 1.5 Concept of operations -- 2 The Data Mining Process -- 2.1 Best practices in knowledge discovery in databases -- 2.2 The scientific method and the paradigms that come with it -- 2.3 How to develop your paradigm -- 2.4 The data mining process methodology -- 2.5 Business understanding -- 2.6 Data understanding -- 2.7 Data preparation -- 2.8 Modeling -- 2.9 Evaluation -- 2.10 Deployment -- 2.11 Performance measurement -- 2.12 Collaborative data mining: the confluence of data mining -- and knowledge management -- 3 Data Mining Tools and Techniques -- 3.1 Microsoft's entry into data mining -- 3.2 The Microsoft data mining perspective -- 3.3 Data mining and exploration (DMX) projects -- 3.4 OLE DB for data mining architecture -- 3.5 The Microsoft data warehousing framework and allian( -- 3.6 Data mining tasks supported by SQL Server 2000 -- Analysis Services -- 3.7 Other elements of the Microsoft data mining strategy -- 4 Managing the Data Mining Project -- 4.1 The mining mart -- 4.2 Unit of analysis -- 4.3 Defining the level of aggregation -- 4.4 Defining metadata -- 4.5 Calculations -- 4.6 Standardized values -- 4.7 Transformations for discrete values -- 4.8 Aggregates -- 4.9 Enrichments -- 4.10 Example process (target marketing) -- 4.11 The data mart -- 5 Modeling Data -- S. I The database -- 5.2 Problem scenario -- 5.3 Setting up analysis services -- 5.4 Defining the OLAP cube -- 5.5 Adding to the dimensional representation -- 5.6 Building the analysis view for data mining -- 5.7 Setting up the data mining analysis -- 5.8 Predictive modeling (classification) tasks -- 5.9 Creating the mining model -- 5.10 The tree navigator -- 5.1 I Clustering (creating segments) with clusteranalysis -- 5.12 Confirming the model through validation -- 5.13 Summary -- 6 Deploying the Results -- 6.1 Deployments for predictive tasks (classification) -- 6.2 Lift charts -- 6.3 Backing up and restoring databases -- 7 The Discovery and Delivery of Knowledge for Effective -- Enterprise Outcomes: Knowledge Management -- 7.1 The role of implicit and explicit knowledge -- 7.2 A primer on knowledge management -- 7.3 The Microsoft technology-enabling framework -- 7.4 Summary -- Appendix A: Glossary -- Appendix B: References -- Appendix C: Web Sites -- Appendix D: Data Mining and Knowledge Discovery -- Data Sets in the Public Domain -- Appendix E: Microsoft Solution Providers -- Appendix F: Summary of Knowledge Management -- Case Studies and Web Locations -- Index.
630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title OLE (Computer file)
9 (RLIN) 3096
630 00 - SUBJECT ADDED ENTRY--UNIFORM TITLE
Uniform title SQL server.
9 (RLIN) 3097
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
9 (RLIN) 3098
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified Publisher description
Uniform Resource Identifier <a href="http://www.loc.gov/catdir/description/els031/00047514.html">http://www.loc.gov/catdir/description/els031/00047514.html</a>
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://www.aginternetwork.net/whalecomwww.sciencedirect.com/whalecom0/science/book/9781555582425">http://www.aginternetwork.net/whalecomwww.sciencedirect.com/whalecom0/science/book/9781555582425</a>
856 4# - ELECTRONIC LOCATION AND ACCESS
Materials specified Table of Contents
Uniform Resource Identifier <a href="http://www.loc.gov/catdir/toc/fy02/00047514.html">http://www.loc.gov/catdir/toc/fy02/00047514.html</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type eBook
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Total Checkouts Full call number Date last seen Uniform Resource Identifier Price effective from Koha item type Public note
    Library of Congress Classification     Meru University Meru University Open Shelves 26/04/2012   QA76.9.D343 D43 2001 26/04/2012 http://www.aginternetwork.net/whalecomwww.sciencedirect.com/whalecom0/science/book/9781555582425 26/04/2012 eBook Seek AGORA user name and password from the library.

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