Data mining models /David L. Olson. (Record no. 73587)

MARC details
000 -LEADER
fixed length control field 03301nam a2200469 i 4500
001 - CONTROL NUMBER
control field 11231819
003 - CONTROL NUMBER IDENTIFIER
control field CaPaEBR
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240726104638.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160715s2016 nyua foab 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781631575495
Qualifying information
040 ## - CATALOGING SOURCE
Original cataloging agency CaBNVSL
Language of cataloging eng
Description conventions rda
Transcribing agency CaBNVSL
Modifying agency CaBNVSL
050 04 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76
Item number .D383 2016
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Olson, David L.,
Dates associated with a name 1944-,
Relator term Author
245 10 - TITLE STATEMENT
Title Data mining models /David L. Olson.
250 ## - EDITION STATEMENT
Edition statement First edition.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York, New York (222 East 46th Street, New York, NY 10017) :
Name of publisher, distributor, etc. Business Expert Press,
Date of publication, distribution, etc. (c)2016.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (172 pages) :
Other physical details illustrations.
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
347 ## - DIGITAL FILE CHARACTERISTICS
File type data file
Source rda
490 1# - SERIES STATEMENT
Series statement Big data and business analytics collection,
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note
505 00 - FORMATTED CONTENTS NOTE
Formatted contents note 1. Data mining in business --
Title 2. Business data mining tools --
-- 3. Data mining processes and knowledge discovery --
-- 4. Overview of data mining techniques --
-- 5. Data mining software --
-- 6. Regression algorithms in data mining --
-- 7. Neural networks in data mining --
-- 8. Decision tree algorithms --
-- 9. Scalability --
-- Notes --
-- References --
-- Index.
520 3# - SUMMARY, ETC.
Summary, etc. Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to first describe the benefits of data mining in business, describe the process and typical business applications, describe the workings of basic data mining models, and demonstrate each with widely available free software. The book focuses on demonstrating common business data mining applications. It provides exposure to the data mining process, to include problem identification, data management, and available modeling tools. The book takes the approach of demonstrating typical business data sets with open source software. KNIME is a very easy-to-use tool, and is used as the primary means of demonstration. R is much more powerful and is a commercially viable data mining tool. We will demonstrate use of R through Rattle. We also demonstrate WEKA, which is a highly useful academic software, although it is difficult to manipulate test sets and new cases, making it problematic for commercial use. We will demonstrate methods with a small but typical business dataset. We use a larger (but still small) realistic business dataset for Chapter 9.
530 ## - COPYRIGHT INFORMATION:
COPYRIGHT INFORMATION COPYRIGHT NOT covered - Click this link to request copyright permission:
Uniform Resource Identifier <a href="b">b</a>
530 ## - COPYRIGHT INFORMATION:
COPYRIGHT INFORMATION
538 ## - SYSTEM DETAILS NOTE
System details note Mode of access: World Wide Web.
538 ## - SYSTEM DETAILS NOTE
System details note System requirements: Adobe Acrobat reader.
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note Title from PDF title page (viewed on July 15, 2016).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Business
General subdivision Data processing.
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term big data
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term business analytics
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term clustering
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term data mining
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term decision trees
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term neural network models
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term regression models
856 41 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000538.html">https://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000538.html</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type
DONATED BY:
VENDOR Business Expert Press
Classification part QA76.9.D343
PUBLICATION YEAR (c)2016
LOCATION
REQUESTED BY:
--
-- NFIC
-- Cynthia Snell
902 ## - LOCAL DATA ELEMENT B, LDB (RLIN)
a 1
b Cynthia Snell
c 1
d Cynthia Snell
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Uniform Resource Identifier Price effective from Koha item type
        Non-fiction G. Allen Fleece Library G. Allen Fleece Library   03/20/2023 Business Expert Press   QA76.9.D343 11231819 03/20/2023 https://go.openathens.net/redirector/ciu.edu?url=https://portal.igpublish.com/iglibrary/search/BEPB0000538.html 03/20/2023 Online Book (LOGIN USING YOUR MY CIU LOGIN AND PASSWORD)