Discuss the similarity between a k-nearest neighbor classifier in traditional machine learning and the user-based collaborative filtering algorithm. Describe an analogous classifier to item-based collaborative filtering.
Added by Leonard C.
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It works by finding a predetermined number of training samples closest in distance to the new point, and predicting the label from these. The number of samples can be a user-defined constant (k-nearest neighbor learning), or vary based on the local density of Show more…
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