Authors:
(1) Troisemaine Colin, Department of Computer Science, IMT Atlantique, Brest, France., and Orange Labs, Lannion, France;
(2) Reiffers-Masson Alexandre, Department of Computer Science, IMT Atlantique, Brest, France.;
(3) Gosselin Stephane, Orange Labs, Lannion, France;
(4) Lemaire Vincent, Orange Labs, Lannion, France;
(5) Vaton Sandrine, Department of Computer Science, IMT Atlantique, Brest, France.
In the previous sections, we presented the models, the hyperparameter optimization and the estimation procedure of the number of novel classes independently. In this section, these components are brought together to form a complete training procedure. To ensure that no prior knowledge about the novel classes is ever used in this process, the number of novel classes is naturally estimated during the k-fold CV introduced in Section 4. As the whole process is quite complex, we try to summarize it in clear terms in this section and in Algorithm 1.