6. A customer advocacy agency, Equitable Ernest, is interested in providing a service in which an individual can estimate their own credit care (a continuous measure used by banks, insurance companies, and other businesses when granting loans, quoting premiums, and issuing credit). The dataset creditscore contains data on an individual's credit score and other variables. (A) Create a k-means clustering using all variables in the clustering, standardizing the variables and using 10 clusters. In this structure, the smallest frequency in any cluster is 9 and the largest frequency in any cluster is 1. The largest distance between two cluster centroids is 0.6925. 3414 24124 5 4414 4215420 IT 1 04MI38 HomeOwner OVER ALL 1.79177 01836 0 604151 Approximeh Copocked Our-Al B-Squad : 1:4131(B) Repeat this k-means clustering using only credit score in the clustering, with 10 clusters. In this structure, the smallest frequency in any cluster is 4 and the largest frequency in any cluster is 6. The largest distance between two cluster centroids is 0.7112 Cluster Summary Maximum Distance from Seed Radius Distance Between Cluster Frequency RMS Sid Deviation to Observation Exceeded Nearest Cluster Cluster Centroids 0. 1985 0 5541 2 591 0 2013 0.4519 0.7112 0 2189 2. 1621 0.27 19 7 102 0.48-45 1 1474 D. 1907 0.3427 9 015878 D 2925 0.5434 4 63 D.1454 0.3369 9 1.7055 271 0 2121 Statistics for Variables Variable Total STD Within STD R-Square 83041-R50) CreditScore 0 20347 0 958675 23. 1983 12 OVER-ALL 1.10800 0.20347 0958575 23. 198312 Pseudo F Statistic = 12559 26 Approximate Expected Over-All R-Squared . |0.95005 (c) which clustering method do you believe would be best to use? Include a few sentences on why you made that selection. Option B would be the best selection for clustering. Option B has the smallest distance between Cluster centroids