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Tesi etd-02192020-165904

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Tipo di tesi
Tesi di laurea magistrale
URN
etd-02192020-165904
Titolo
On the use of sequential learning models to estimate natural selection on HIV from clinical samples
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Parole chiave
  • gru
  • hiv
  • machine learning
  • selection coefficient
Data inizio appello
06/03/2020
Consultabilità
Tesi non consultabile
Riassunto (Inglese)
Riassunto (Italiano)
The thesis deals with the analysis of artificial and real-world clinical data concerning natural selection on the HIV virus. A sampling algorithm has been implemented to generate synthetic data for preliminary validation and training set expansion. A recurrent neural architecture has been deployed, trained and tested on the task of estimating the selection coefficient in the HIV virus.
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Tesi non consultabile.
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