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

• Κύριοι συγγραφείς: Basuchoudhary, Atin (Συγγραφέας), Bang, James T. (Συγγραφέας), Sen, Tinni (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Σειρά: SpringerBriefs in Economics,
• Θέματα: Data mining.; Application software.; Econometrics.; Game theory.; Economic growth.; Economics.; Economic Growth.; Data Mining and Knowledge Discovery.; Game Theory.; Computer Appl. in Social and Behavioral Sciences.
• Φυσική περιγραφή: VI, 94 p. 20 illus., 19 illus. in color. online resource.
• ISBN: 9783319690148
• ISSN: 2191-5504

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. .