The nearest neighbor algorithm is one that employs instance-based learning – it stores the training data to use for the determination of classification for pieces of data as it encounters them. The algorithm computes the Euclidean distance between the instances to help it compare them with the training data to find their nearest neighbors. The method applies to situations when the classifications are discrete numerical values, and a vector can define instances.
Explain how the nearest neighbor algorithm works.
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