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A Taiwan-based credit card issuer wants to better predict the likelihood of default for its customers,

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A Taiwan-based credit card issuer wants to better predict the likelihood of default for its customers, as well as identify the key drivers that determine this likelihood. It would help the issuer have a better understanding of their current and potential customers, which would inform their future strategy,

 

including their planning of offering targeted credit products to their customers. Perform the comparative analysis of the problem stated on the following machine learning models in R and RapidMiner: (Any two). Use the payment default (or no default) as the dependent variable. 1. Logistic Regression 2. KNN 3. Decision Tree The criteria for comparison are Confusion Matrix, Time Taken and Accuracy Percentage.

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