Econom\'etrie et Machine Learning

 0 Người đánh giá. Xếp hạng trung bình 0

Tác giả: Arthur Charpentier, Emmanuel Flachaire, Antoine Ly

Ngôn ngữ: eng

Ký hiệu phân loại: 133.5833 Astrology

Thông tin xuất bản: 2017

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 161568

Comment: in FrenchEconometrics and machine learning seem to have one common goal: to construct a predictive model, for a variable of interest, using explanatory variables (or features). However, these two fields developed in parallel, thus creating two different cultures, to paraphrase Breiman (2001). The first was to build probabilistic models to describe economic phenomena. The second uses algorithms that will learn from their mistakes, with the aim, most often to classify (sounds, images, etc.). Recently, however, learning models have proven to be more effective than traditional econometric techniques (with a price to pay less explanatory power), and above all, they manage to manage much larger data. In this context, it becomes necessary for econometricians to understand what these two cultures are, what opposes them and especially what brings them closer together, in order to appropriate tools developed by the statistical learning community to integrate them into Econometric models.
Tạo bộ sưu tập với mã QR

THƯ VIỆN - TRƯỜNG ĐẠI HỌC CÔNG NGHỆ TP.HCM

ĐT: (028) 36225755 | Email: tt.thuvien@hutech.edu.vn

Copyright @2024 THƯ VIỆN HUTECH