K Means Clustering Algorithm | K Means Solved Numerical Example | Euclidean Distance by Mahesh Huddar
In this tutorial, we will learn the K-Means clustering algorithm, one of the most popular unsupervised machine learning algorithms, with this step-by-step guide and solved example using Euclidean distance.
Suppose that the data mining task is to cluster points into three clusters, where the points are
A1(2, 10), A2(2, 5), A3(8, 4), B1(5, 8), B2(7, 5), B3(6, 4), C1(1, 2), C2(4, 9).
The distance function is Euclidean distance.
Suppose initially we assign A1, B1, and C1 as the center of each cluster, respectively.
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