Get Your Data Ready For Machine Learning in R with Pre-Processing

Last Updated on August 22, 2019

Preparing data is required to get the best results from machine learning algorithms.

In this post you will discover how to transform your data in order to best expose its structure to machine learning algorithms in R using the caret package.

You will work through 8 popular and powerful data transforms with recipes that you can study or copy and paste int your current or next machine learning project.

Kick-start your project with my new book Machine Learning Mastery With R, including step-by-step tutorials and the R source code files for all examples.

Let’s get started.

Need For Data Pre-Processing

You want to get the best accuracy from machine learning algorithms on your datasets.

Some machine learning algorithms require the data to be in a specific form. Whereas other algorithms can perform better if the data is prepared in a specific way, but not always. Finally, your raw data
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