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Mastering Data analysis with R

You're reading from   Mastering Data analysis with R Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization

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Product type Paperback
Published in Sep 2015
Publisher Packt
ISBN-13 9781783982028
Length 396 pages
Edition 1st Edition
Languages
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Author (1):
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Gergely Daróczi Gergely Daróczi
Author Profile Icon Gergely Daróczi
Gergely Daróczi
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Table of Contents (17) Chapters Close

Preface 1. Hello, Data! FREE CHAPTER 2. Getting Data from the Web 3. Filtering and Summarizing Data 4. Restructuring Data 5. Building Models (authored by Renata Nemeth and Gergely Toth) 6. Beyond the Linear Trend Line (authored by Renata Nemeth and Gergely Toth) 7. Unstructured Data 8. Polishing Data 9. From Big to Small Data 10. Classification and Clustering 11. Social Network Analysis of the R Ecosystem 12. Analyzing Time-series 13. Data Around Us 14. Analyzing the R Community A. References Index

Summary

In this chapter, we covered a number of ways to deal with multivariate data to reduce the number of available dimensions in the means of artificially computed continuous variables and to identify underlying, latent, and similarly numeric variables. On the other hand, sometimes it's rather difficult to describe reality with numbers and we should rather think in categories.

The next chapter will introduce new methods to define data types (clusters) and will also demonstrate how to classify elements with the help of available training data.

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