How is the effect of a low or high value of K in K-Nearest Neighbor smoothing related to the low or high value of k in Trimmed Mean smoothing?
Added by Raul R.
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It works by replacing each data point with the average of its K nearest neighbors. The value of K determines the number of neighbors used for smoothing. A low value of K means that only a few neighbors are considered, while a high value of K means that more Show more…
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