I have another question about semi-supervised learning vs unsupervised clustering, what are the benefits and limitations?
I have got some data with labels and some without labels. I performed semi-supervised learning (using SVM classifier) for the classification task.
Also, I compared with the results of using unsupervised clustering (hierarchical clustering). I found that:
For the labeled data, the clustering results are quite similar to the cross-validation performance of the semi-supervised learning.
However, for the unlabeled data, the clustering results are not as good as the further prediction of the trained SVM classifier (using labeled data as aforementioned) according to some qualitative checking (visually check the classified images).
Howe to interpret these findings? Does this mean that semi-supervised learning method is superior to unsupervised learning? And why?