This chapter introduced a wide variety of ways to cluster and classify data, discussed which analysis procedures and models are very important, and generally used elements of a data scientist's toolbox. In the next chapter, we will focus on a less general, but still important, field— how to analyze graphs and network data.
Mastering Data analysis with R
By :
Mastering Data analysis with R
By:
Overview of this book
Table of Contents (19 chapters)
Mastering Data Analysis with R
Credits
www.PacktPub.com
Preface
Free Chapter
Hello, Data!
Getting Data from the Web
Filtering and Summarizing Data
Restructuring Data
Building Models (authored by Renata Nemeth and Gergely Toth)
Beyond the Linear Trend Line (authored by Renata Nemeth and Gergely Toth)
Unstructured Data
Polishing Data
From Big to Small Data
Classification and Clustering
Social Network Analysis of the R Ecosystem
Analyzing Time-series
Data Around Us
Analyzing the R Community
References
Customer Reviews