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Table 4 Example of creation of 60 cluster features by the dummy method

From: Airline new customer tier level forecasting for real-time resource allocation of a miles program

k Example of K-means output (categorical) Label of the new binary features Binary value
2 “B” Cluster_k2_A 0
Cluster_k2_B 1
3 “A” Cluster_k3_A 1
Cluster_k3_B 0
Cluster_k3_C 0
5 “C” Cluster_k5_A 0
Cluster_k5_B 0
Cluster_k5_C 1
Cluster_k5_D 0
Cluster_k5_E 0
7 “C” Cluster_k7_A 0
Cluster_k7_B 0
Cluster_k7_C 1
Cluster_k7_D 0
Cluster_k7_E 0
Cluster_k7_F 0
Cluster_k7_G 0
10 “A” Cluster_k10_A 1
Cluster_k10_K 0
20 “A” Cluster_k20_A 1
Cluster_k20_T 0