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> |
-- |
Click here to access this RESOURCE ONLINE | Login using your my.ciu username & password |
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 |