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Learning Predictive Analytics with R

You're reading from  Learning Predictive Analytics with R

Product type Book
Published in Sep 2015
Publisher Packt
ISBN-13 9781782169352
Pages 332 pages
Edition 1st Edition
Languages
Author (1):
Eric Mayor Eric Mayor
Profile icon Eric Mayor

Table of Contents (23) Chapters

Learning Predictive Analytics with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Setting GNU R for Predictive Analytics Visualizing and Manipulating Data Using R Data Visualization with Lattice Cluster Analysis Agglomerative Clustering Using hclust() Dimensionality Reduction with Principal Component Analysis Exploring Association Rules with Apriori Probability Distributions, Covariance, and Correlation Linear Regression Classification with k-Nearest Neighbors and Naïve Bayes Classification Trees Multilevel Analyses Text Analytics with R Cross-validation and Bootstrapping Using Caret and Exporting Predictive Models Using PMML Exercises and Solutions Further Reading and References Index

Summary


In this chapter, we have examined a number of possible ways to explore data visually. We have used the flexibility of R to produce samples programmatically to generate data on the fly, which we have used to illustrate how to use basic plots. We have examined some of the associations in the game of roulette and developed functions according to our analytical needs. We have also examined how to recode data, and use only a subset of data, and introduced the concept of multiple sampling.

The next chapter will deal with more advanced graphs using the lattice package. This comes in handy when dealing with several group memberships (for example, ethnicity and gender at once).

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