Perform k-means clustering with the number of clusters

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Reference no: EM131307245

Data Mining Review Questions - XLMiner Labs - Cluster Analysis1. Marketing to Frequent Flyers. The file EastWestAirlinesCluster.xls contains information on 4000 passengers who belong to the airline's frequent flier program. For each passenger, the data include information on the passenger's mileage history, and on different ways that mileage was accrued or spent in the last year. The goal is try to identify clusters of passengers who have similar characteristics, for the purpose of targeting different segments for different types of mileage offers. So I'll ask you one more time, "What's in your wallet?" (textbook reference - 15.4).

a. Perform k-means clustering with the number of clusters set to five (5). Be sure to Normalize the Input Data.

b. Which cluster(s) are the best formed and why? Which cluster(s) are the poorest formed and why?

c. Which two clusters have the greatest distance between them?

d. What cluster would you target for an offer? Why did you select that cluster?
(Hint: Review the coordinates on the KMC_Output1 tab)

e. What offer(s) would you send to the customers in the cluster identified in Part d? Why?

Attachment:- Cluster.xls

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The task is about on k-mean clustering on XLMiner with the given dataset. I had done k-mean clustering on XLMiner according to the given instructions. After doing practical, analysis of the output is also done in detail. I had written answers to every question according to the generated output of the k-means clustering. Along with this, proper referencing and in-text citation is also done in the task.

Reference no: EM131307245

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Data Mining Lab - Attach below are the lab requirement, data set file, and study material - Claritas segmented US neighborhoods based on demographics & income: “Bohemian Mix,” “Furs & station wagons,” “Money & Brains,”

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