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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
Concepts
Author (1):
Eric Mayor Eric Mayor
Profile icon Eric Mayor
LinkedIn
Eric Mayor is a senior researcher and lecturer at the University of Neuchatel, Switzerland. He is an enthusiastic user of open source and proprietary predictive analytics software packages, such as R, Rapidminer, and Weka. He analyzes data on a daily basis and is keen to share his knowledge in a simple way.
See other products by 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 seen how k-NN and Naïve Bayes work by programming our own implementation of the algorithms. You have discovered how to perform these analyses in R. We have shown you that it is not optimal to test our classifier with the data it has been trained with. We have seen that the number of neighbors selected in k-NN impacts the performance of the classification and examined different performance measures. In the next chapter, you will learn about decision trees.

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Authors (1)

Profile icon Eric Mayor
LinkedIn
Eric Mayor is a senior researcher and lecturer at the University of Neuchatel, Switzerland. He is an enthusiastic user of open source and proprietary predictive analytics software packages, such as R, Rapidminer, and Weka. He analyzes data on a daily basis and is keen to share his knowledge in a simple way.
See other products by Eric Mayor

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