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R for Data Science by Dan Toomey

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Summary

In this chapter, we discussed different aspects of clustering using R. We used a couple of different methods to select the number of clusters. We used k-means clustering, which appears to be the most prevalent tool in use. We used medoids clustering, another popular choice. We also looked into Bayesian clustering, an interesting choice for this type of data. Lastly, we looked at affinity clustering.

In the next chapter, we will cover the graphics functionality available in R.

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