Algorithm 2: (Few-shot AI corrector [83]: 1NN version. Deployment). Input: a data vector $\mathit{x}$, the set’s $\mathcal{X}$ centroid vector $\overline{\mathit{x}}$, matrices H, W, the number of clusters, k, cluster centroids ${\overline{\mathit{y}}}_1,\dots ,{\overline{\mathit{y}}}_k$, threshold, $\theta$ (or thresholds ${\theta }_1,\dots ,{\theta }_k$), discriminant vectors, ${\mathit{w}}_i$, $i=1,\dots ,k$.

Compute $${\mathit{x}}_w=WH(\mathit{x}-\overline{\mathit{x}})$$ Determine $$\ell =arg\underset{i}{min}\parallel {\mathit{x}}_w-{\overline{\mathit{y}}}_i\parallel .$$ Associate the vector $\mathit{x}$ with the set $\mathcal{Y}$ if $({\mathit{w}}_{\ell },{\mathit{x}}_w)>\theta$ and with the set $\mathcal{X}$ otherwise. If multiple thresholds are given then associate the vector $\mathit{x}$ with the set $\mathcal{Y}$ if $({\mathit{w}}_{\ell },{\mathit{x}}_w)>{\theta }_{\ell }$ and with the set $\mathcal{X}$ otherwise. Output: a label attributed to the vector $\mathit{x}$.