The text of the chapter shows how one can transform any linear classifier into recognizing nonlinear decision boundaries by using a feature engineering phase in which the eigenvectors of an appropriately chosen similarity matrix are used to create new features. Discuss the impact of this type of preprocessing on the nature of the clusters found by the k-means algorithm.