16.5: Semi-Supervised Learning
- Page ID
- 41012
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In some scenarios we have a data set with only a few labeled data points, a large number of unlabeled data points and inherent structure in the data. This type of scenario both clustering and classification do not perform well and a hybrid approach is required. This semi-supervised approach could involve the clustering of data first followed by the classification of the generated clusters.