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Neural Networks In Organizational Research Applying Pattern Recognition To The Analysis Of Organizational Behavior 1st Edition David Scarborough

  • SKU: BELL-4644720
Neural Networks In Organizational Research Applying Pattern Recognition To The Analysis Of Organizational Behavior 1st Edition David Scarborough
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Neural Networks In Organizational Research Applying Pattern Recognition To The Analysis Of Organizational Behavior 1st Edition David Scarborough instant download after payment.

Publisher: Amer Psychological Assn
File Extension: PDF
File size: 9.07 MB
Pages: 187
Author: David Scarborough, Mark John Somers
ISBN: 9781591474159, 1591474159
Language: English
Year: 2006
Edition: 1

Product desciption

Neural Networks In Organizational Research Applying Pattern Recognition To The Analysis Of Organizational Behavior 1st Edition David Scarborough by David Scarborough, Mark John Somers 9781591474159, 1591474159 instant download after payment.

While the term neural networks may be unfamiliar to many organizational psychologists, exciting new applications of artificial intelligence are attracting notice among organizational behavior researchers. In Neural Networks in Organizational Research: Applying Pattern Recognition to the Analysis of Organizational Behavior, authors David Scarborough and Mark Somers bring researchers, academics, and practitioners up to speed on this emerging field, in which powerful computing capabilities offer new insights into longstanding, complex I/O questions such as employee selection and behavioral prediction. Neural networks mimic the way the human brain works, using interconnected nodes and feedback loops to learn to recognize even subtle patterns in vast amounts of data. They can process data far more quickly and efficiently than conventional techniques can, and produce better empirical results. They are especially useful for modeling nonlinear processes. The book traces the development of this methodology and demonstrates how it opens up new ways of thinking about traditional problems. Academic researchers will gain a design template for studying both the linear and non-linear elements of a given problem, and thus enhance their own research

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