Data released from the US department of Commerce, Bureau of the Census is available in R (see, data(state) ).
(a) Focus on the data Population, Income, Illiteracy, Life Exp, Murder, HS Grad, Frost, Area. Cluster this data using hierarchical clustering. Keep the class labels (region, or state name) in mind, but do not use them in the modeling. Report your detailed findings. ** You may have done this step in an earlier assignment.
(b) Focus on the data Population, Income, Illiteracy, Life Exp, Murder, HS Grad, Frost, Area. Cluster this data using SOM. Keep the class labels (region, or state name) in mind, but do not use them in the modeling. Report your detailed findings. ** You may have done this step in an earlier assignment.
(c) Build a Gaussian Graphical Model using the Graphical Lasso for Population, Income, Illiteracy, Life Exp, Murder, HS Grad, Frost, Area. What do you find for different penalties, and how does it compliment (and/or contradict) your results in part A and B?
(d) Describe some of the advantages of clustering to GGMs in the context of this problem, and more generally.