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Nearest-Neighbor Learning Algorithm

  • Learning is just storing the representations of the training examples in D.

  • Testing instance x (under 1NN):

    • Compute similarity between x and all examples in D.

    • Assign x the category of the most similar example in D.

  • Does not explicitly compute a generalization or category prototypes.

  • Also called:

    • Case-based learning

    • Memory-based learning

    • Lazy learning

  • Rationale of kNN: contiguity hypothesis


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