Timeline for Best method to assign new customers to existing clusters after segmentation?
Current License: CC BY-SA 3.0
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| when toggle format | what | by | license | comment | |
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| Dec 6, 2020 at 2:40 | history | edited | kjetil b halvorsen♦ |
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| Feb 16, 2015 at 19:56 | answer | added | ee2Dev | timeline score: 4 | |
| Feb 16, 2015 at 15:08 | comment | added | GeorgeOfTheRF | Thanks. Calculate Euclidean distance of new customer to centroid of each cluster and assigning to cluster with least distance. Is this better approach than building a classification model which gives probability of being in each of the clusters? | |
| Feb 16, 2015 at 14:26 | comment | added | Cagdas Ozgenc | Since you used k-means you already assumed that each component of the customer information is equally important. So you can either continue like that, i.e. match the new customer with euclidean distance to cluster centers, or think of what the gain/loss of misclassification will be? | |
| Feb 16, 2015 at 14:14 | history | asked | GeorgeOfTheRF | CC BY-SA 3.0 |