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R for Data Science by Dan Toomey

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Summary

In this chapter, we discussed different methods of determining patterns in data. We found patterns in a dataset using the eclat function looking for similar patterns in a population. We used a TraMineR to find frequent sets of items in a market basket. We used apriori rules to determine associations among items in a market basket. We used TraMineR to determine sequences of career transition among adults and visualized the same with extensive graphics features available for sequence data. Finally, we examined the similarities and differences between the sequences using seqdist.

In the next chapter, we will cover text mining or examining datasets that are text-based, rather than numerical or categorical.

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