Publication: Entropy Triangles: An application to measuring the transmission of entropy in Autoencoders
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2019-10
Defense date
2019-10-14
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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.
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Keywords
Deep Neural Networks, Information Bottleneck, Autoencoder, Entropy Triangle, Classifcation, Data Science