no code implementations • 25 Jun 2017 • Wiem Elghazel, Kamal Medjaher, Nourredine Zerhouni, Jacques Bahi, Ahamd Farhat, Christophe Guyeux, Mourad Hakem
The aim of this article is ($1$) to show that random forests are relevant in this context, due to their flexibility and robustness, and ($2$) to provide first examples of use of this method for diagnostics based on data provided by a wireless sensor network.