Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/181389
Title: | Mètodes i models per a l'anàlisi de clústers |
Author: | Morera de Frutos, Marc |
Director/Tutor: | Fortiana Gregori, Josep |
Keywords: | Anàlisi de conglomerats Treballs de fi de grau Anàlisi multivariable Mineria de dades Algorismes computacionals Cluster analysis Bachelor's theses Multivariate analysis Data mining Computer algorithms |
Issue Date: | 24-Jan-2021 |
Abstract: | [en] In this project we study clustering methods, focusing on the two most used classes of algorithms: partitional and hierarchical. We explore definition and performance of several methods, as well as some criteria to validate results. Then, we assess computational problems arising from adapting generic clustering methods to tackle large data sets, as well as algorithms designed with the goal of improving their performance in these cases. We include R code to demonstrate practical applications of clustering and to generate graphical visualizations. |
Note: | Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2021, Director: Josep Fortiana Gregori |
URI: | http://hdl.handle.net/2445/181389 |
Appears in Collections: | Programari - Treballs de l'alumnat Treballs Finals de Grau (TFG) - Matemàtiques |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
tfg_marc_morera_de_frutos.pdf | Memòria | 1.62 MB | Adobe PDF | View/Open |
codi_font.rar | Codi font | 796.56 kB | Unknown | View/Open |
This item is licensed under a Creative Commons License