As a consequence, the maximum number of eigenvectors in the supervised KPCA model is the minimum of the number of features and the number of vectors from the labeled training corpus, while the maximum number of eigenvectors for the semi-supervised KPCA model is the minimum of the number of features and total number of vectors from the combined labeled and unlabeled training corpora.
assume a training corpus of the eight sentences as shown in Table 2, adapted from Senseval-2 English lexical sample corpus.