Consider the following four 2-dimensional data points: (2, 2), (4, 4), (1, 5) and (5, 1). We can make use of the KL-Transform to find a transformed subspace containing a cluster. Let L be the total number of dimensions in the original space and K be the total number of dimensions in the projected subspace. Please illustrate the KL-transform technique with the above example when L = 2 and K = 1. Note: You need to show the covariance matrix, eigenvalues and eigenvectors, and the transformation step in your solution.