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A practical guide to data mining for business and industry / (Record no. 64637)

MARC details
000 -LEADER
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001 - CONTROL NUMBER
control field sulb-eb0032985
003 - CONTROL NUMBER IDENTIFIER
control field BD-SySUS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20170713221350.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 131212s2014 enk ob 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2013049413
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
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Transcribing agency DLC
Modifying agency YDX
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019 ## -
-- 905245061
-- 929527020
-- 959867764
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-- 962668632
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781118763377
Qualifying information (electronic bk.)
International Standard Book Number 1118763378
Qualifying information (electronic bk.)
International Standard Book Number 9781118763728
Qualifying information (electronic bk.)
International Standard Book Number 1118763726
Qualifying information (electronic bk.)
International Standard Book Number 9781118763704
Qualifying information (electronic bk.)
International Standard Book Number 111876370X
Qualifying information (electronic bk.)
Canceled/invalid ISBN 1306550696
Canceled/invalid ISBN 9781306550697
Canceled/invalid ISBN 1119977134
Canceled/invalid ISBN 9781119977131
029 1# - OTHER SYSTEM CONTROL NUMBER (OCLC)
OCLC library identifier CHBIS
System control number 010259582
OCLC library identifier CHNEW
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OCLC library identifier CHVBK
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OCLC library identifier DEBBG
System control number BV042682891
OCLC library identifier DEBSZ
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OCLC library identifier DEBSZ
System control number 446580929
OCLC library identifier NZ1
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OCLC library identifier NZ1
System control number 15626494
OCLC library identifier NZ1
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OCLC library identifier DEBBG
System control number BV043625852
OCLC library identifier AU@
System control number 000052331730
OCLC library identifier DEBBG
System control number BV043396403
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)865297935
Canceled/invalid control number (OCoLC)905245061
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037 ## - SOURCE OF ACQUISITION
Stock number CL0500000570
Source of stock number/acquisition Safari Books Online
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HF5415.125
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 000000
Source bisacsh
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/12
Edition number 23
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Ahlemeyer-Stubbe, Andrea.
245 12 - TITLE STATEMENT
Title A practical guide to data mining for business and industry /
Statement of responsibility, etc. Andrea Ahlemeyer-Stubbe, Shirley Coleman.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Chichester, West Sussex, United Kingdom :
Name of producer, publisher, distributor, manufacturer John Wiley & Sons Inc.,
Date of production, publication, distribution, manufacture, or copyright notice 2014.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
588 0# - SOURCE OF DESCRIPTION NOTE
Source of description note Print version record and CIP data provided by publisher.
520 ## - SUMMARY, ETC.
Summary, etc. "Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest."--
Assigning source Unedited summary from book.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Title page; Copyright page; Glossary of terms; Part I: Data mining concept; 1 Introduction; 1.1 Aims of the Book; 1.2 Data Mining Context; 1.3 Global Appeal; 1.4 Example Datasets Used in This Book; 1.5 Recipe Structure; 1.6 Further Reading and Resources; 2 Data mining definition; 2.1 Types of Data Mining Questions; 2.2 Data Mining Process; 2.3 Business Task: Clarification of the Business Question behind the Problem; 2.4 Data: Provision and Processing of the Required Data; 2.5 Modelling: Analysis of the Data; 2.6 Evaluation and Validation during the Analysis Stage
Formatted contents note 2.7 Application of Data Mining Results and Learning from the ExperiencePart II: Data mining Practicalities; 3 All about data; 3.1 Some Basics; 3.2 Data Partition: Random Samples for Training, Testing and Validation; 3.3 Types of Business Information Systems; 3.4 Data Warehouses; 3.5 Three Components of a Data Warehouse: DBMS, DB and DBCS; 3.6 Data Marts; 3.7 A Typical Example from the Online Marketing Area; 3.8 Unique Data Marts; 3.9 Data Mart: Do's and Don'ts; 4 Data Preparation; 4.1 Necessity of Data Preparation; 4.2 From Small and Long to Short and Wide; 4.3 Transformation of Variables
Formatted contents note 4.4 Missing Data and Imputation Strategies4.5 Outliers; 4.6 Dealing with the Vagaries of Data; 4.7 Adjusting the Data Distributions; 4.8 Binning; 4.9 Timing Considerations; 4.10 Operational Issues; 5 Analytics; 5.1 Introduction; 5.2 Basis of Statistical Tests; 5.3 Sampling; 5.4 Basic Statistics for Pre-analytics; 5.5 Feature Selection/Reduction of Variables; 5.6 Time Series Analysis; 6 Methods; 6.1 Methods Overview; 6.2 Supervised Learning; 6.3 Multiple Linear Regression for Use When Target is Continuous; 6.4 Regression When the Target is Not Continuous; 6.5 Decision Trees
Formatted contents note 6.6 Neural Networks6.7 Which Method Produces the Best Model? A Comparison of Regression, Decision Trees and Neural Networks; 6.8 Unsupervised Learning; 6.9 Cluster Analysis; 6.10 Kohonen Networks and Self-Organising Maps; 6.11 Group Purchase Methods: Association and Sequence Analysis; 7 Validation and Application; 7.1 Introduction to Methods for Validation; 7.2 Lift and Gain Charts; 7.3 Model Stability; 7.4 Sensitivity Analysis; 7.5 Threshold Analytics and Confusion Matrix; 7.6 ROC Curves; 7.7 Cross-Validation and Robustness; 7.8 Model Complexity; Part III: Data mining in action; 8 Marketing
Formatted contents note 8.1 Recipe 1: Response Optimisation: To Find and Address the Right Number of Customers8.2 Recipe 2: To Find the x% of Customers with the Highest Affinity to an Offer; 8.3 Recipe 3: To Find the Right Number of Customers to Ignore; 8.4 Recipe 4: To Find the x% of Customers with the Lowest Affinity to an Offer; 8.5 Recipe 5: To Find the x% of Customers with the Highest Affinity to Buy; 8.6 Recipe 6: To Find the x% of Customers with the Lowest Affinity to Buy; 8.7 Recipe 7: To Find the x% of Customers with the Highest Affinity to a Single Purchase
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
Topical term or geographic name as entry element Marketing
General subdivision Data processing.
Topical term or geographic name as entry element Management
General subdivision Mathematical models.
Topical term or geographic name as entry element COMPUTERS
General subdivision General.
Source of heading or term bisacsh
Topical term or geographic name as entry element Data mining.
Source of heading or term fast
Authority record control number (OCoLC)fst00887946
Topical term or geographic name as entry element Management
General subdivision Mathematical models.
Source of heading or term fast
Authority record control number (OCoLC)fst01007201
Topical term or geographic name as entry element Marketing
General subdivision Data processing.
Source of heading or term fast
Authority record control number (OCoLC)fst01010187
Topical term or geographic name as entry element Marketing - Data processing.
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
Genre/form data or focus term Electronic books.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Print version:
Main entry heading Ahlemeyer-Stubbe, Andrea.
Title Practical guide to data mining for business and industry.
Place, publisher, and date of publication Chichester, West Sussex, United Kingdom : Wiley, 2014
International Standard Book Number 9781119977131
Record control number (DLC) 2013047218
-- (OCoLC)865179974
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://onlinelibrary.wiley.com/book/10.1002/9781118763704">http://onlinelibrary.wiley.com/book/10.1002/9781118763704</a>
Public note Wiley Online Library [Free Download only for SUST IP]
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