In principle, there are two important parameters to the KNeighbors classifier: the number of neighbors and how you measure distance between data points. In practice, using a small number of neighbors like three or five often works well, but you should certainly adjust this parameter. Choosing the right distance measure is somewhat beyond the scope of this book. By default, Euclidean distance is used, which works well in many settings.
what is the euclidean space
Share this highlighthttp://www.safaribooksonline.com/a/introduction-to-machine/11466537/