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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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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Summary

In this chapter, we investigated machine learning in action using R. We learned about breaking up our dataset into a training and testing section. The examples showed how to use the predict method from our models. We generated models using linear regression, stepwise regression, k-nearest neighbor, Naïve Bayes, k-clustering, decision trees, neural net, and the random forest algorithms. We applied tests of the models' effectiveness.

In the next chapter, we will cover predicting events with machine learning.

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