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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