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Tesi etd-11082023-150410


Tipo di tesi
Tesi di laurea magistrale
Autore
BIANCHI, MARIO
Indirizzo email
m.bianchi66@studenti.unipi.it, bianchi.mario@outlook.com
URN
etd-11082023-150410
Titolo
Multivariate Shapelets: a Random Approach for Car Crash Prediction
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Guidotti, Riccardo
relatore Spinnato, Francesco
Parole chiave
  • shapelets
  • xai
  • time series
  • explainability
  • shap
  • multivariate time series
Data inizio appello
01/12/2023
Consultabilità
Non consultabile
Data di rilascio
01/12/2063
Riassunto
After analyzing a neural network used for detecting car accidents, more efficient and interpretable alternatives are proposed. Subsequently, an innovative method based on Multivariate Shapelets is introduced, which can achieve better results than the original neural network efficiently and can be easily interpreted by a third-party operator. Finally, this new method is tested on other datasets to evaluate its performance.
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