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R for Data Science by 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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