OBJECTIVE-Clustering of Iris Dataset
From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
ALGORITHM USED - K-Means
K-means is a centroid-based algorithm, or a distance-based algorithm, where we calculate the distances to assign a point to a cluster. In K-Means, each cluster is associated with a centroid.
Workflow behind Implemention of K-Means Clustering --
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Choose the number of clusters k
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Select k random points from the data as centroids
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Assign all the points to the closest cluster centroid
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Recompute the centroids of newly formed clusters
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Repeat steps 3 and 4