3. Write your own RStudio code to implement the k-means algorithm, consider the following data set consisting of the scores of two variables on each of seven individuals: Subject 2 3 4 5 1.0 1.5 3.0 5.0 3.5 4.5 3.5 2.0 4.0 7.0 5.0 5.0 4.5 7 This data set is to be grouped into two clusters. As a first step in finding a sensible initial partition, let the A & B values of the two individuals furthest apart (using the Euclidean distance measure), assume the initial cluster means: Mean Individua Vector Group 1 Group 2 centroid 1.0, 1.0 5.0, 7.0 4. Apply your RStudio code to assigned to cluster with the closest centroid. Now the initial partition has changed, and the two clusters at this stage having the following characteristics: Mean Individua Vector centroid Cluster 1 1, 2, 3 1.8, 2.3 Cluster 24, 5,6,7(4.1, 5.4 Use your RStudio code to verify the above results