Improved classification of genomic data by Gram-Schmidt feature selection
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Author
Marco Reales, Jose Maria
Other authors
Universitat Ramon Llull. La Salle
Publication date
2010Abstract
This work explains some important aspects in the world of the neural networks, as the
classification methods and the procedures of feature selection. Moreover, there is a
practical part that consists in creating a program that provides us the useful information
to do the classification. It is important to consider that in this thesis we have touched
some biochemical aspects because the program has been designed for bioinformatics
applications. Therefore the first part of the work consists in an introduction to genomics,
namely, relations of enzymes and amino-acids. Finally all the results obtained in the
work have been reported and discussed.
Document Type
Master's final project
Language
English
Subject (CDU)
004 - Computer science and technology. Computing. Data processing
62 - Engineering. Technology in general
Keywords
Xarxes neuronals (Informàtica) -- TFM
Pages
108 p.
Collection
ENG TFM MUEXT; 1865
This item appears in the following Collection(s)
Rights
© Escola Tècnica Superior d'Enginyeria La Salle
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/