K-Means Clustering: Organizing the Grocery Store Aisles
Welcome to the Supermarket: What is K-Means Clustering? Step through the sliding glass doors into a giant, newly built supermarket. Thousands of unorganized product items have just been delivered in unmarked cardboard boxes and dumped in the middle of the floor. You don't have a master directory or pre-labeled inventory list. Your task as store manager is to group similar items together so you can create intuitive shopping aisles: placing apples near oranges, milk near cheese, and detergent near paper towels. Because you are grouping raw items without pre-existing labels, this is an Unsupervised Learning problem. The core algorithm used to organize this supermarket floor is **K-Means Clustering**. Deconstructing K-Means: How the Store Gets Organized The "K" in K-Means stands for the number of groups (aisles) you decide to create, while "Means" refers to the center location of each group. The algorithm works through a simple 4-step...