  Feature selection plays an important role in the data mining process. It is
needed to deal with the excessive number of features, which can become a
computational burden on the learning algorithms. It is also necessary, even
when computational resources are not scarce, since it improves the accuracy of
the machine learning tasks, as we will see in the upcoming sections. In this
review, we discuss the different feature selection approaches, and the relation
between them and the various machine learning algorithms.
