Essay About Clusters Of Passengers And Cluster Centroids

Airfare Prediction Model
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Marketing to Frequent Fliers. The file EastWestAirlinesCluster.xls (available on the textbook website
Question 1.Apply hierarchical clustering with Euclidean distance and Ward’s method. Make sure to standardize the data first. How many clusters appear?Solution.                          Number of clusters: 3Cluster I13162 171014151852019Cluster II3122118941622Cluster III123611242530272928[pic 1]Dendrogram remains constant when cluster was 3 and when no restriction was given to it.What would happen if the data were not standardized?Solution: Balance, Bonus miles and Days since enrolled will take higher weights hence the result will be skewed towards those variables. Ex- Predicted Clusters will be as follows:[pic 2]Balance, Bonus miles and Days since enrolled will take higher weights hence the result will be skewed towards those variables. C) Compare the cluster centroids to characterize the different clusters and try to give each cluster a label.Solution.Cluster 1Less frequent FliersCluster 2Frequent fliers Clusters 3Intermittent Fliers: Between cluster 1 and 3 hence Customers group for promotions[pic 3]To check the stability of the clusters, remove a random 5% of the data (by taking a random sample of 95% of the records), and repeat the analysis. Does the same picture emerge?Solution. Part AStructure of the Dendrogram remained same but there was a change noticed in the formation of clusters. [pic 4]Part bTotal 3999less 5% 3790Removed209Count Where Cluster1 = cluster 2 Count Where Sub cluster 1= Sub cluster 2 13682743999034%ID which remained constant after removing 5 % of data