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in k means clustering how to find the distance between two points. Distance measures will help to find the similarity between two elements and it will influence the shape of the clusters. Points 1 and 5 have not change so the distance between these two points are the same than in previous step.
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So we use the idea of approximation using Lloyds Algorithm. That means two centroids. Randomly select any K data points as cluster centers.
So we use the idea of approximation using Lloyds Algorithm.
In this post we calculate clusters with the k-means clustering algorithm. We use this method to measure the distance between two integer or floating points real-valued points. Calculate the center of both the formed clusters and shift the centroids there. Our goal is to predict k centroids and a label c i for each datapoint.
