In the semi-supervised KPCA model, training vectors are drawn from both the labeled training corpus and a much larger unlabeled training corpus.
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.