Coverart for item
The Resource Building better models with JMP Pro, Jim Grayson, Sam Gardner, Mia L. Stephens

Building better models with JMP Pro, Jim Grayson, Sam Gardner, Mia L. Stephens

Label
Building better models with JMP Pro
Title
Building better models with JMP Pro
Statement of responsibility
Jim Grayson, Sam Gardner, Mia L. Stephens
Creator
Contributor
Author
Subject
Language
eng
Summary
This book provides an example-based introduction to business analytics, with a proven process that guides you in the application of modeling tools and concepts. It gives you the "what, why, and how" of using JMP Pro for building and applying analytic models. It will greatly benefit faculty members who teach any of the following subjects at the lower to upper graduate level: predictive modeling, data mining, and business analytics. Novice to advanced users in business statistics, business analytics, and predictive modeling will find that it provides a peek inside the black box of algorithms and the methods used. Topics include: regression, logistic regression, classification and regression trees, neural networks, model cross-validation, model comparison and selection, and data reduction techniques. --
Assigning source
Edited summary from book
Cataloging source
CtWfDGI
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Building better models with JMP Pro, Jim Grayson, Sam Gardner, Mia L. Stephens
Label
Building better models with JMP Pro, Jim Grayson, Sam Gardner, Mia L. Stephens
Publication
Copyright
Related Contributor
Related Location
Related Agents
Related Authorities
Related Subjects
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
mixed
Content category
text
Content type code
txt
Content type MARC source
rdacontent
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781629599564&userID=ebsco-test&password=ebsco-test
Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4359697'}
Extent
1 online resource
Form of item
online
Isbn
9781629599564
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations
Specific material designation
remote

Library Locations

    • Folsom LibraryBorrow it
      110 8th St, Troy, NY, 12180, US
      42.729766 -73.682577
Processing Feedback ...