I've been working with a dataset containing handwritten numbers, and to classify what number it is I've used KNN. I've made a plot comparing validation with training misclassification rate for each K = [1, 30], see below.
My question is the following: The optimal model should be picked based on the lowest validation error, but in my plot there's two values of K which yields the same misclassification error. So is there a correct approach to this or is it something up to me to decide?
As I can think of it is
A) chose K = 4 as a higher K yields a less complex model.
B) Chose K = 3 as this is the K which corresponds to the turning point when the model no longer improves as we're testing on new data.