Machine-learning Techniques in Economics New Tools for Predicting Economic Growth

Machine-learning Techniques in Economics New Tools for Predicting Economic Growth / by Atin Basuchoudhary, James T. Bang, Tinni Sen.

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technolo...

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Bibliographic Details
Main Authors: Basuchoudhary, Atin (Author), Bang, James T. (Author), Sen, Tinni (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Series:SpringerBriefs in Economics,
Springer eBook Collection.
Subjects:
Economic growth.
Econometrics.
Data mining.
Game theory.
Application software.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary:This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer economic questions. While machine learning itself is not a new idea, advances in computing technology combined with a dawning realization of its applicability to economic questions makes it a new tool for economists. .
Physical Description:VI, 94 p. 20 illus., 19 illus. in color. online resource.
ISBN:9783319690148
ISSN:2191-5504
DOI:10.1007/978-3-319-69014-8

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