A small and easy introduction to Transductive Learning

Input: a) A set of labelled examples where every is the input vector, and is the corresponding output label. Output: The set of expected labels for all instances in . There are two ways (or rather, two philosophies) you could use, to solve this problem. Induction, in the context of learning, is the attempted discovery of rules/generalizations based on analysis of collected data. 'Attempted discovery' is the key term here – the generalizations are not facts, but approximations based on evidence you have gathered.