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Machine Learning with R Quick Start Guide

You're reading from   Machine Learning with R Quick Start Guide A beginner's guide to implementing machine learning techniques from scratch using R 3.5

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781838644338
Length 250 pages
Edition 1st Edition
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Author (1):
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Iván Pastor Sanz Iván Pastor Sanz
Author Profile Icon Iván Pastor Sanz
Iván Pastor Sanz
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Summary

In this chapter, we have learned some initial important steps to prepare and understand our data. How many variables are available in our dataset? What kind of information do we have? Are there some missing values in the data? How can I treat missing values and outliers? I hope you can now answer these questions.

Moreover, in this chapter, we also learned how to split our data to train and validate our forthcoming predictive model. In the next chapter, we will advance one step ahead, performing a univariate analysis on this data, which means analyzing whether variables are useful for predicting bank failures.

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