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R Data Analysis Cookbook - Second Edition by Kuntal Ganguly

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K-means clustering suffers when you have a large dataset (or lots of variables) and is also highly sensitive to outliers due to the use of the mean in the cluster centroid calculation. We will look at some other partitioning clustering algorithms to overcome the shortcomings of kmeans in the coming sections.

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