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Data Analysis with R, Second Edition

You're reading from   Data Analysis with R, Second Edition A comprehensive guide to manipulating, analyzing, and visualizing data in R

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Length 570 pages
Edition 2nd Edition
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Author (1):
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Tony Fischetti Tony Fischetti
Author Profile Icon Tony Fischetti
Tony Fischetti
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Table of Contents (19) Chapters Close

Preface 1. RefresheR FREE CHAPTER 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data To Reason About The World 6. Testing Hypotheses 7. Bayesian Methods 8. The Bootstrap 9. Predicting Continuous Variables 10. Predicting Categorical Variables 11. Predicting Changes with Time 12. Sources of Data 13. Dealing with Missing Data 14. Dealing with Messy Data 15. Dealing with Large Data 16. Working with Popular R Packages 17. Reproducibility and Best Practices 18. Other Books You May Enjoy

Exercises

Practice the following exercises to revise the concepts learned in this chapter:

  • How did we waste computation in the similarity_matrix function?
  • Both the Last.fm and the MusicBrainz API have a count value associated with each tag, which can be taken to represent the extent to which the tag applied to the artist. By ignoring this field, in both cases we implicitly used a count of 1 for every tag, making well-fitting tags just as important as relatively less well-fitting ones. Rewrite the code to take count into account, and weigh each tag proportionally to its count value. This will be challenging, but it will be invaluable for understanding the material. It will also boost your confidence as an R programmer once you finish. Go you!
  • How else might you be able to extend and improve upon our ragtag recommender system?
  • The efficient market hypothesis posits that since the...
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