Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/98886
Title: | Estudio de predictores de felicidad a nivel mundial |
Author: | Jimbo Granda, María Augusta |
Director: | Rius, Àngels |
Tutor: | Iglesias Allones, Jose Luis |
Abstract: | The main objective of developing this project is to discover key factors that make people happier, for which a data mining model has been designed and built. The data considered in the development of this project have been obtained from historical surveys corresponding to the years 2015, 2016 and 2017 in more than 100 countries worldwide. The six main factors that appear in each of the datasets and that serve to assess happiness in each country are: economic production, social support, life expectancy, freedom, absence of corruption and generosity. For the analysis of the data of the report, machine learning and data mining techniques are used, the programming has been developed in the R language. According to the results obtained, the following key questions are concluded or answered: What are the main factors that contribute to happiness?- Are there important differences in these factors between countries? - Are there differences in happiness in the three years? - Are there relations between the different regions according to the level of happiness? - In which region are the happiest and least happy countries in the world?. |
Keywords: | data mining key factors happiness |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2019 |
Publication license: | http://creativecommons.org/licenses/by-nc-sa/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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mjimboTFM0319memoria.pdf | Memoria del TFM | 1,68 MB | Adobe PDF | View/Open |
mjimboTFM0319presentación.pdf | Presentación del TFM | 1,71 MB | Adobe PDF | View/Open |
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