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R for Data Science by Dan Toomey

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Summary

In this chapter, we discussed cluster analysis, anomaly detection, and association rules. In cluster analysis, we use k-means clustering, k-medoids clustering, hierarchical clustering, expectation-maximization, and density estimation. In anomaly detection, we found outliers using built-in R functions and developed our own specialized R function. For association rules, we used the apriori package to determine the associations amongst datasets.

In the next chapter, we will cover data mining for sequences.

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