TY  - BOOK
AU  - Basuchoudhary,Atin
AU  - Bang,James T.
AU  - Sen,Tinni
ED  - SpringerLink (Online service)
TI  - Machine-learning Techniques in Economics: New Tools for Predicting Economic Growth  
T2  - SpringerBriefs in Economics,
SN  - 9783319690148
AV  - HD72-88 
U1  - 338.9 23
PY  - 2017///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Economic growth
KW  - Econometrics
KW  - Data mining
KW  - Game theory
KW  - Application software
KW  - Economic Growth
KW  - Data Mining and Knowledge Discovery
KW  - Game Theory
KW  - Computer Appl. in Social and Behavioral Sciences
N1  - Why this Book? -- Data, Variables, and Their Sources -- Methodology -- Predicting Economic Growth: A First Look -- Predicting Economic Growth: Which Variables Matter? -- Predicting Recessions: What We Learn from Widening the Goalposts -- Epilogue; Available to subscribing member institutions only. Доступно лише організаціям членам підписки
N2  - 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. 
UR  - https://doi.org/10.1007/978-3-319-69014-8
ER  -