Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Unsupervised learning for economic risk evaluation in the context of
  Covid-19 pandemic   Justifying draconian measures during the Covid-19 pandemic was difficult not
only because of the restriction of individual rights, but also because of its
economic impact. The objective of this work is to present a machine learning
approach to identify regions that should implement similar health policies. For
that end, we successfully developed a system that gives a notion of economic
impact given the prediction of new incidental cases through unsupervised
learning and time series forecasting. This system was built taking into account
computational restrictions and low maintenance requirements in order to improve
the system's resilience. Finally this system was deployed as part of a web
application for simulation and data analysis of COVID-19, in Colombia,
available at (https://covid19.dis.eafit.edu.co).

7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
17
The categories of this paper are: q-fin
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol