A Machine Learning Analysis of COVID-19 Mental Health Data. (arXiv:2112.00227v2 [cs.LG] UPDATED)

In late December 2019, the novel coronavirus (Sars-Cov-2) and the resulting
disease COVID-19 were first identified in Wuhan China. The disease slipped
through containment measures, with the first known case in the United States
being identified on January 20th, 2020. In this paper, we utilize survey data
from the Inter-university Consortium for Political and Social Research and
apply several statistical and machine learning models and techniques such as
Decision Trees, Multinomial Logistic Regression, Naive Bayes, k-Nearest
Neighbors, Support Vector Machines, …

analysis arxiv covid covid-19 data health health data learning machine machine learning mental health