In a previous post we saw the differences between K-means and K-NN. Here is step by step on how to compute K-nearest neighbors KNN algorithm. Determine parameter K = number of nearest neighbors Calculate the distance between the query-instance and all the training samples Sort the distance and determine nearest neighbors based on the K-th minimum distance Gather the category of the nearest neighbors Use simple majority of the category of nearest neighbors as the prediction…

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## Pattern Recognition

*Browsing*