In this context, MC takes as input a portion of a matrix whose row/column indices refer to countries/products, respectively, while the matrix elements refer to the value of exports. As a result, MC will predict for all remaining country/product pairs (c, p) whether RCA ≥ 1 or not.
Jul 21, 2023
Sep 8, 2021 · This work applies Matrix Completion (MC) -- a class of machine-learning methods commonly used in the context of recommendation systems -- to analyse economic ...
In this framework, this article addresses the issue of the interpretability of results obtained with a machine learning technique—namely, matrix completion—when ...
This work applies Matrix Completion – a class of machine-learning methods commonly used in the context of recommendation systems – to analyze economic ...
This work applies Matrix Completion (MC) -- a class of machine-learning methods commonly used in the context of recommendation systems -- to analyse ...
Matrix completion of world trade: An analysis of interpretability through Shapley values ; Published date, 01 September 2023 ; Author, Giorgio Gnecco,Federico ...
Nov 15, 2021 · MC is applied to reconstruct the Revealed Comparative Advantage (RCA) matrix, whose elements express the relative advantage of countries in ...
This work applies Matrix Completion (MC) – a class of machine-learning methods commonly used in recommendation systems – to analyze economic complexity. In this ...
Sep 8, 2021 · PDF | This work applies Matrix Completion (MC) -- a class of machine-learning methods commonly used in the context of recommendation systems ...
Jun 10, 2022 · This work applies Matrix Completion (MC) – a class of machine-learning methods commonly used in recommendation systems – to analyze economic complexity.