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Applied Predictive Modeling (Record no. 44737)

MARC details
000 -LEADER
fixed length control field 04396nam a22004577a 4500
001 - CONTROL NUMBER
control field sulb-eb0022645
003 - CONTROL NUMBER IDENTIFIER
control field BD-SySUS
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20160413122311.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130517s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461468493
-- 978-1-4614-6849-3
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-1-4614-6849-3
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA276-280
072 #7 - SUBJECT CATEGORY CODE
Subject category code PBT
Source bicssc
Subject category code MBNS
Source bicssc
Subject category code MED090000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kuhn, Max.
Relator term author.
245 10 - TITLE STATEMENT
Title Applied Predictive Modeling
Medium [electronic resource] /
Statement of responsibility, etc. by Max Kuhn, Kjell Johnson.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York, NY :
Name of producer, publisher, distributor, manufacturer Springer New York :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2013.
300 ## - PHYSICAL DESCRIPTION
Extent XIII, 600 p. 203 illus., 153 illus. in color.
Other physical details 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
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note General Strategies -- Regression Models -- Classification Models -- Other Considerations -- Appendix -- References -- Indices.
520 ## - SUMMARY, ETC.
Summary, etc. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages.  Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development.  He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D.  His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning.  The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems.  Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance—all of which are problems that occur frequently in practice.   The text illustrates all parts of the modeling process through many hands-on, real-life examples.  And every chapter contains extensive R code for each step of the process.  The data sets and corresponding code are available in the book’s companion AppliedPredictiveModeling R package, which is freely available on the CRAN archive.   This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses.  To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package.   Readers and students interested in implementing the methods should have some basic knowledge of R.  And a handful of the more advanced topics require some mathematical knowledge.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Statistics.
Topical term or geographic name as entry element Statistics for Life Sciences, Medicine, Health Sciences.
Topical term or geographic name as entry element Statistics and Computing/Statistics Programs.
Topical term or geographic name as entry element Statistics, general.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Johnson, Kjell.
Relator term author.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9781461468486
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-1-4614-6849-3">http://dx.doi.org/10.1007/978-1-4614-6849-3</a>
912 ## -
-- ZDB-2-SMA
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type

No items available.