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JKISeason2-2
https://www.knime.com/just-knime-it

Challenge 02: Segmentation of Credit Card Users
Level: Medium

Description: Credit Card company ABC maintains information about customer purchases and payments. The information is available for individual customers as Payments Info and Purchase Info. The company wants to segment the customers into three (3) clusters, so that marketing campaigns can be designed according to each cluster. You are asked to use both infos together to build a clustering model that adequately segments the customers. What patterns do customers in the same cluster have in common? Also, Information for newly registered customers is available. You are asked to assign cluster labels to newly registered customers using the trained clustering model, and then export the results into a CSV file. Do the assignments make sense? How do you assess their quality?

Author: Mahantesh Pattadkal

Dataset: Customer Data on Kaggle

Node 770/30medianNode 10Node 11Node 12Node 13Node 14Node 15Node 17Node 18Node 19Node 20Node 50Node 51Node 52Node 53Node 54Node 55Node 56Node 57CSV Reader Partitioning Missing Value Normalizer PCA Compute PCA Apply k-Means Joiner SilhouetteCoefficient Sorter Pivoting Column Rename(Regex) Bar Chart Column Rename(Regex) SilhouetteCoefficient Sorter Bar Chart Pivoting Normalizer (Apply) PCA Apply Cluster Assigner Component Component Node 770/30medianNode 10Node 11Node 12Node 13Node 14Node 15Node 17Node 18Node 19Node 20Node 50Node 51Node 52Node 53Node 54Node 55Node 56Node 57CSV Reader Partitioning Missing Value Normalizer PCA Compute PCA Apply k-Means Joiner SilhouetteCoefficient Sorter Pivoting Column Rename(Regex) Bar Chart Column Rename(Regex) SilhouetteCoefficient Sorter Bar Chart Pivoting Normalizer (Apply) PCA Apply Cluster Assigner Component Component

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