Unsupervised Machine Learning for anomalies detection, clustering and synthetic data generation of household appliances consumptions - WebThesis

WebThesis

Unsupervised Machine Learning for anomalies detection, clustering and synthetic data generation of household appliances consumptions

Nicola Barletta

Unsupervised Machine Learning for anomalies detection, clustering and synthetic data generation of household appliances consumptions.

Rel. Edoardo Patti, Andrea Acquaviva, Luciano Baresi. Politecnico di Torino, Master of science program in Computer Engineering, 2019

Relators

Edoardo Patti, Andrea Acquaviva, Luciano Baresi

Academic year

2019/20

Publication type

Electronic

Number of Pages

124

Additional Information

Tesi secretata. Fulltext non presente

Course of studies

Master of science program in Computer Engineering

Classe di laurea

New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING

URI

https://webthesis.biblio.polito.it/id/eprint/13124

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