In regards to machine learning; in k-nearest neighbors (KNN), the classification is achieved by majority vote in the vicinity of data. Suppose there are two classes of data each of n / 2 points overlapped to some extent in a 2-dimensional space. Describe what happens to the training error (using all available data) when the neighbor size k varies from n to 1.