Use this link to cite:
http://hdl.handle.net/2183/31209 Estudio de los datos de evolución del SARS-CoV-2 en Galicia a través de diferentes fuentes de datos en el primer trimestre del año 2021
Loading...
Identifiers
Publication date
Authors
Alvariño Arias, Diego
Advisors
Other responsabilities
Enxeñaría informática, Grao en
Journal Title
Bibliographic citation
Type of academic work
Academic degree
Abstract
[Resumen] El objetivo de este Trabajo de Fin de Grado es analizar los datos de evolución del SARS-CoV-2
en Galicia, dividida en siete áreas sanitarias, a través de diferentes fuentes de datos investigadas,
centrándonos en el primer trimestre del año 2021.
Para alcanzar el objetivo marcado, se ha seguido una metodología propia de trabajos de investigación
de datos y sus respectivos pasos adaptados al estudio a realizar, la metodología
CRISP-DM.
Principalmente, después de un esfuerzo por normalizar, tratar y explicar un conjunto de datos
razonable y trabajado, siguiendo todos los pasos necesarios y marcados por la metodología,
se han estudiado diferentes modelos de predicción. Además, se ha empleado la tarea clustering
con aprendizaje no supervisado, basada en k-means para llegar a unas conclusiones y
resultados finales de un análisis descriptivo.
[Abstract] The objective of this Final Degree Project is to analyze the evolution data of SARS-CoV-2 in Galicia, divided into seven health areas, through different sources of data investigated, focusing on the first quarter of the year 2021. To achieve the established objective, a methodology of data research work has been followed and its respective steps adapted to the study to be carried out, the CRISP-DM methodology. Mainly, after an effort to normalize, treat and explain a reasonable and worked data set, following all the necessary steps and marked by the methodology, different prediction models have been studied. In addition, the clustering task with unsupervised learning, based on kmeans, has been used to reach conclusions and final results of a descriptive analysis.
[Abstract] The objective of this Final Degree Project is to analyze the evolution data of SARS-CoV-2 in Galicia, divided into seven health areas, through different sources of data investigated, focusing on the first quarter of the year 2021. To achieve the established objective, a methodology of data research work has been followed and its respective steps adapted to the study to be carried out, the CRISP-DM methodology. Mainly, after an effort to normalize, treat and explain a reasonable and worked data set, following all the necessary steps and marked by the methodology, different prediction models have been studied. In addition, the clustering task with unsupervised learning, based on kmeans, has been used to reach conclusions and final results of a descriptive analysis.







