Boruta package

One of the most known wrapper packages in R is called Boruta. This package is mainly based on the algorithm of random forests.

Although this algorithm will be explained in more detail later in the book, Boruta, proposed by Breiman in 2001, is a tool that mines data and generates many decision trees on the samples and combines them by majority voting. The purpose of random forests creating different decision trees is to acquire the best possible classifications from different classes of data. 

One example of a successful implementation of random forests is in credit card fraud detection systems.

In the Boruta package, randomized variables are created using multiple combinations of other variables in the dataset.

New variables ...

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