Okay-Means Clustering is likely one of the first algorithms I utilized in machine studying. Throughout my Grasp’s diploma, one in all my seniors requested me to assist him with clustering as a result of he knew I used to be into machine studying. I searched on the web and came upon concerning the Okay-Means algorithm. By looking out extra, I discovered a pair extra articles — some had math, some used Python, and a few had visualizations. So I considered writing a whole publish about okay means utilizing python and math introduction.
This text will stroll you thru the implementation of Okay-Means clustering in Python utilizing a dataset of buyer spending habits. It would additionally clarify the ideas behind it that will help you perceive how the algorithm works.
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Okay-Means clustering is an algorithm that teams knowledge into Okay distinct clusters based mostly on their options. It really works iteratively to assign knowledge factors to one in all Okay clusters, minimizing the variance inside every cluster. Every cluster is represented by its centroid, and the purpose is to attenuate the space between the information factors and their respective cluster centroids.