semi-supervised-learning
The data set is massive but the labeled sample are few
Training strategy:
- we train a model with the labeled data, then we apply the model to predict the unlabeled data
- first cluster the images into groups (unsupervised learning), and then apply the supervised learning algorithm on each of the groups individually