Predictive data mining models (Record no. 565871)

MARC details
000 -LEADER
fixed length control field 01696nam a22002057a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 241120b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811396663
Paper back/Hardbound pbk
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312
Item number OLS
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Olson, David L
245 ## - TITLE STATEMENT
Title Predictive data mining models
Statement of responsibility, etc / David L. Olson and Desheng Wu
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Springer
Name of publisher Singapore
Year of publication 2020
300 ## - PHYSICAL DESCRIPTION
Number of Pages xi, 125 p.
Other physical details ill.
Dimensions 23 cm.
490 ## - SERIES STATEMENT
Series statement Computational risk management
520 ## - SUMMARY, ETC.
Summary, etc This book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R) and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Business Data processing
Topical Term Data Mining
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Reference
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Full call number Accession Number Price effective from Koha item type
        Anna Centenary Library Anna Centenary Library 3RD FLOOR, A WING 21.08.2024 006.312 OLS 697901 21.08.2024 Reference

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