Regulation Modelling and Analysis Using Machine Learning During the Covid-19 Pandemic in Russia.
Stud Health Technol Inform
; 285: 259-264, 2021 Oct 27.
Article
in English
| MEDLINE | ID: covidwho-1502267
ABSTRACT
Due to the specific circumstances related to the COVID-19 pandemic, many countries have enforced emergency measures such as self-isolation and restriction of movement and assembly, which are also directly affecting the functioning of their respective public health and judicial systems. The goal of this study is to identify the efficiency of the criminal sanctions in Russia that were introduced in the beginning of COVID-19 outbreak using machine learning methods. We have developed a regression model for the fine handed out, using random forest regression and XGBoost regression, and calculated the features importance parameters. We have developed classification models for the remission of the penalty and for setting a sentence using a gradient boosting classifier.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pandemics
/
Machine Learning
/
COVID-19
Type of study:
Observational study
/
Randomized controlled trials
Limits:
Humans
Country/Region as subject:
Asia
/
Europa
Language:
English
Journal:
Stud Health Technol Inform
Journal subject:
Medical Informatics
/
Health Services Research
Year:
2021
Document Type:
Article
Affiliation country:
SHTI210610
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