Unless I am not understanding something, this appears to have multiple incorrect statements in it, for instance: > It first identifies the k points in the trai

Unless I am not understanding something, this appears to have multiple incorrect statements in it, for instance: > It first identifies the k points in the training data that are closest to the test value and calculates the distance between all those categories. The test value will belong to the category whose distance is the least. There is no distance measure in deciding a category. The distance measure is used to find the N nearest neighbors. Once those neighbors are found, the class of the new data point is assigned based on the relative number of entities of each class in the N neighbor set (always taken as the most common class in the neighbor set, as far as I am aware).