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R for Data Science

You're reading from   R for Data Science Learn and explore the fundamentals of data science with R

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781784390860
Length 364 pages
Edition 1st Edition
Languages
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (14) Chapters Close

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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