Classification of medical data using Restricted Boltzmann Machines
Aalto, Markku (2014)
Aalto, Markku
2014
Tietojenkäsittelyoppi - Computer Science
Informaatiotieteiden yksikkö - School of Information Sciences
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Hyväksymispäivämäärä
2014-03-17
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:uta-201403261270
https://urn.fi/URN:NBN:fi:uta-201403261270
Tiivistelmä
Restricted Boltzmann Machines are generative models commonly used for feature extraction and for training deep neural networks. In this thesis, their applicability for classification of medical data is researched. Three different approaches are evaluated using two small medical data sets. It is shown that the resulting classifiers are able to form sensible models of the data, having competitive performance when compared to other methods on these data sets.