Machine Learning with R Cookbook - Second Edition

How it works...

In this recipe, we demonstrate how different costs can affect the SVM classifier. First, we create an iris subset with the columns Sepal.Length, Sepal.Width, and Species containing the species, setosa and virginica. Then, in order to create a soft margin and allow some misclassification, we use an SVM with a small cost (where cost = 1) to train the support of the vector machine. Next, we circle the support vectors with blue circles and add the separation line. As per the preceding figure, one of the green points (virginica) is misclassified (it is classified to setosa) to the other side of the separation line due to the choice of the small cost.

In addition to this, we would like to determine how a large cost can affect the ...