K-Nearest Neighbors (KNN)

1. Overview

K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions)

2. Description

2.1 Procedure

• Step 1: Choose the number K of neighbors

• Step 2: Take the K nearest neighbors of the new data point, according to the Euclidean distance

• Step 3: Among these K neighbors, count the number of data points in each category

• Step 4: Assign the new data point to the category where you counted the most neighbors

3. Reference

https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

https://www.saedsayad.com/k_nearest_neighbors.htm

https://www.youtube.com/watch?v=UqYde-LULfs