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http://hdl.handle.net/10609/53366
Title: | Implementació d'una xarxa neural configurable amb optimització genètica |
Author: | Mas Mateo, Jordi |
Tutor: | Isern, David |
Others: | Ventura, Carles |
Abstract: | In this work, a multilayer perceptron neural network will be implemented, hyperparameters of which will be tuned by a genetic algorithm, that will try to find a near-optimal configuration for a given dataset. This is a proof of concept that will merge two algorithms inspired by nature: neural networks that imitates biological neurons operation, and genetic algorithms that mimics the natural selection. Algorithms like that had been proposed and studied before, but does not exist any implementation of it for the R statistical software. Thus, the final product of this work is an R package that will be distributed under the GPL. |
Keywords: | neural network hyperparameters genetic algorithms |
Document type: | info:eu-repo/semantics/bachelorThesis |
Issue Date: | 1-Jun-2016 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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JordiMas_TFG_0616.zip | Producte | 37,64 MB | ZIP | View/Open |
jordimasTFG0716memòria.pdf | Memòria del TFG | 1,11 MB | Adobe PDF | View/Open |
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