Nearest Neighbor Classification

Nearest Neighbor Classification is a simple method used to identify the category of a new data point based on its closest existing example. Imagine locating a new city on a map: you look for the nearest city with known characteristics. If most nearby cities are in a particular region, you categorize the new city similarly. Essentially, the algorithm measures how similar the new data is to existing data points, and assigns the category of the closest one. It's an intuitive way to classify data based on proximity, relying on the idea that similar things are situated near each other in the data space.