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Explain the Algorithm Technique of Transduction in Machine Learning?
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Answer / Manojeet Goldar
Transduction is a type of machine learning that focuses on making predictions for new instances based solely on their neighboring instances. In contrast to induction, which makes predictions based on all available training data, transduction only considers the local structure around the instance being predicted. Transduction can be useful when dealing with large datasets or when computational resources are limited. An example of a transductive learning algorithm is transductive support vector machines.
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