Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/83566
Title: | Influence of imbalanced datasets in the induction of Full Bayesian Classifiers |
Author: | Morán Jiménez, Daniel |
Tutor: | Solanas Gómez, Agustí |
Keywords: | Bayesian networks machine learning imbalance |
Issue Date: | 15-Jul-2018 |
Publisher: | Universitat Oberta de Catalunya (UOC) |
Abstract: | This project consists in three main tasks: first, an analysis of the current state of the art in technologies for dealing with class imbalance problems in machine learning algorithms. Second, the analysis of how this problem actually affects a particular class of statistical models, the Bayesian Classifiers, proposing solutions to the particular problems found. And third, to implement a Bayesian Classifier and develop a series of experiments that would support the assertions of the analysis, and shed more light on how this problem can be dealt with. |
Language: | |
URI: | http://hdl.handle.net/10609/83566 |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
dmoranjiTFM0718memory.pdf | Memory of TFM | 6,29 MB | Adobe PDF | ![]() View/Open |
Share:


This item is licensed under a Creative Commons License