MARC details
000 -LEADER |
fixed length control field |
03541cam a2200433 a 4500 |
001 - CONTROL NUMBER |
control field |
BD-DhNSU-29066 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
NSUL-eBook |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20231019143230.0 |
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
fixed length control field |
m\\\\\o\\d\\\\\\\\ |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
201018s2012 flua b b 001 0 eng |
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
LC control number |
2011014298 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781439860915 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
978-1-4398-6092-2 (eBook) |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
DLC |
Transcribing agency |
BD-DhNSU |
Modifying agency |
BD-DhNSU |
041 ## - LANGUAGE CODE |
Language code of text |
eng |
050 00 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
HF5415.126 |
Item number |
.B78 2011 |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
658.8/72 |
Edition number |
22 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Ratner, Bruce. |
245 10 - TITLE STATEMENT |
Title |
Statistical and machine-learning data mining : |
Remainder of title |
techniques for better predictive modeling and analysis of big data / |
Statement of responsibility, etc |
Bruce Ratner. |
250 ## - EDITION STATEMENT |
Edition statement |
2nd ed. |
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
Boca Raton : |
Name of producer, publisher, distributor, manufacturer |
CRC Press, |
Date of production, publication, distribution, manufacture, or copyright notice |
c2011 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
1 online resource (xxv, 516 p.) |
336 ## - CONTENT TYPE |
Source |
rdacontent |
Content type term |
text |
Content type code |
txt |
337 ## - MEDIA TYPE |
Source |
rdamedia |
Media type term |
computer |
Media type code |
c |
500 ## - GENERAL NOTE |
General note |
Rev. ed. of: Statistical modeling and analysis for database marketing. c2003. |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc. note |
Includes bibliographical references and index. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has completely revised, reorganized, and repositioned the original chapters and produced 14 new chapters of creative and useful machine-learning data mining techniques. In sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature.<br/><br/><br/>The statistical data mining methods effectively consider big data for identifying structures (variables) with the appropriate predictive power in order to yield reliable and robust large-scale statistical models and analyses. In contrast, the author's own GenIQ Model provides machine-learning solutions to common and virtually unapproachable statistical problems. GenIQ makes this possible — its utilitarian data mining features start where statistical data mining stops.<br/><br/><br/>This book contains essays offering detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. They address each methodology and assign its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with. |
526 0# - STUDY PROGRAM INFORMATION NOTE |
Program name |
Mathematics, Physics & Statistics |
590 ## - LOCAL NOTE (RLIN) |
Documentalist |
Md. Abdul Hakim |
590 ## - LOCAL NOTE (RLIN) |
Documentalist |
Miron Khan |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Database marketing |
General subdivision |
Statistical methods. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Data mining |
General subdivision |
Statistical methods. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Big data |
General subdivision |
Statistical methods. |
655 #7 - INDEX TERM--GENRE/FORM |
Source of term |
local |
Genre/form data or focus term |
Electronic books. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Ratner, Bruce. |
Relator term |
author |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Public note |
Full text available: |
Materials specified |
◉ login required |
Uniform Resource Identifier |
https://opac.northsouth.edu/cgi-bin/koha/opac-retrieve-file.pl?id=1f2ff6074937f81c2bd888037babdb0f |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
lcc |
Koha item type |
EBOOK |
999 ## - SYSTEM CONTROL NUMBERS (KOHA) |
-- |
29066 |
-- |
29066 |