Machine Learning Project 11 — Whose my Neighbor? — k Nearest Neighbor

Whose my nearest neighbor? — source pixabay.com

Today we will understand the k-Nearest Neighbor (kNN) classification algorithm. It is one of the most easiest algorithms.

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• Let’s say we have identified 2 categories in our dataset — say “Red Category 1” and “Green Category 2” as shown below.

image source: A-Z Machine Learning Udemy

• Now let’s say we add a new data point in our dataset as shown below. So the question is — does it belong to “Red Category 1” or “Green Category 2”. How do we classify this new data point?

image source: A-Z Machine Learning Udemy

So this is where the k Nearest Neighbor (kNN) algorithm will come in to assist us. It’s a very simple algorithm.

• First we have to decide on the number of k neighbors — the most common or default value for k is 5.
• Next, we need to find the 5 nearest neighbors to this new data point based on Euclidean distance or Manhattan distance or any other. In layman’s terms, we have to find the 5 data points that are closest…