Espionage 发表于 2025-3-21 16:38:09

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Peak-Bone-Mass 发表于 2025-3-21 22:20:25

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conifer 发表于 2025-3-22 00:55:14

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不爱防注射 发表于 2025-3-22 07:10:06

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表两个 发表于 2025-3-22 11:50:35

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厚颜无耻 发表于 2025-3-22 14:26:49

Predicting Recessions: What We Learn from Widening the Goalposts,ct” growth variables to check whether these variables are better at predicting recessions. We show how prediction performance of algorithms differs widely depending on the type of prediction criteria. We can, however, identify some of the most salient predictors of recessions. These suggest that fis

Latency 发表于 2025-3-22 20:52:44

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Debark 发表于 2025-3-22 23:57:39

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BOGUS 发表于 2025-3-23 02:13:15

,Predicting a Country’s Growth: A First Look,o validate different growth models. We suggest that validated algorithms enhance the confidence academics should place on any given theoretical growth model. We then show how machine learning can help researchers understand what kinds of concepts may make theoretical growth models more complete.

羊栏 发表于 2025-3-23 07:08:28

Book 2017 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. .
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查看完整版本: Titlebook: Machine-learning Techniques in Economics; New Tools for Predic Atin Basuchoudhary,James T. Bang,Tinni Sen Book 2017 The Author(s) 2017 Mach