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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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 Toomey Toomey
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Toomey
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Toc

Table of Contents (19) Chapters Close

R for Data Science
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Data Mining Patterns 2. Data Mining Sequences FREE CHAPTER 3. Text Mining 4. Data Analysis – Regression Analysis 5. Data Analysis – Correlation 6. Data Analysis – Clustering 7. Data Visualization – R Graphics 8. Data Visualization – Plotting 9. Data Visualization – 3D 10. Machine Learning in Action 11. Predicting Events with Machine Learning 12. Supervised and Unsupervised Learning Index

Questions


Factual

  • How will you exclude white people from the eclat results?

  • Describe the different transitions that occur in the sequence plots.

  • In the TraMineRmvad data summary, there are marked differences in regional responses. Can you guess why?

When, how, and why?

  • Describe what is going on with the few outliers in seqiplot. There are several data points that don't seem to fit.

  • What would be going on in the data presented in seqHtplot when the line curves upward?

  • How will you apply the sequence finding routines discussed?

Challenges

  • Determine what the item numbers represent in the market basket data.

  • The TraMineR package includes much more than what was covered in this chapter. You could investigate the additional functionality further.

You have been reading a chapter from
R for Data Science
Published in: Dec 2014
Publisher:
ISBN-13: 9781784390860
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