#semi-supervised classification

How to Build a Labelled Training Data Set with a Few Labelled Examples

When building a classifier, we assume a large enough training data set with labels is available. This situation is what we call as supervised learning. In a real world setting, such training examples with labels need to be acquired. In any application domain where labeling requires domain expertise such as in medicine, gathering a large training set with labels is an expensive and time consuming…