Publication: Entropy Triangles: An application to measuring the transmission of entropy in Autoencoders
dc.contributor.advisor | Valverde Albacete, Francisco José | |
dc.contributor.author | Luis García, Adrián Manuel de | |
dc.contributor.departamento | UC3M. Departamento de Teoría de la Señal y Comunicaciones | es |
dc.date.accessioned | 2020-04-20T07:54:27Z | |
dc.date.available | 2020-04-20T07:54:27Z | |
dc.date.issued | 2019-10 | |
dc.date.submitted | 2019-10-14 | |
dc.description.abstract | The aim of this Bachelor’s Thesis is to test the functionalities of the Entropy Trian- gle. The Entropy Triangle is a tool designed to analyse the fow of information on a variable after it has been processed by means of a transformation, a classifcation, or any other type method that may have shaped its informational characteristics. The appropri- ate environment has been created with the objective to obtain an accurate profle of such properties, selecting three diferent datasets with a wide variety of traits that allow for our tool to display its more interesting features. The experiments performed include an in-depth analysis of their results and its impacts on the data science feld. | es |
dc.description.degree | Ingeniería en Tecnologías de Telecomunicación | es |
dc.identifier.uri | https://hdl.handle.net/10016/30147 | |
dc.language.iso | eng | es |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.rights.accessRights | open access | es |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject.eciencia | Telecomunicaciones | es |
dc.subject.other | Deep Neural Networks | es |
dc.subject.other | Information Bottleneck | es |
dc.subject.other | Autoencoder | es |
dc.subject.other | Entropy Triangle | es |
dc.subject.other | Classifcation | es |
dc.subject.other | Data Science | es |
dc.title | Entropy Triangles: An application to measuring the transmission of entropy in Autoencoders | es |
dc.type | bachelor thesis | * |
dspace.entity.type | Publication |
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