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Training
Basically non-existing. Store the training samples and maybe perform some preprocessing to speed up queries (feature extraction, dimensionality reduction)

Testing
For classification look at the k nearest neighbors and pick the class with the most votes.

For regression average the values of the k nearest neighbors.