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Problem : Help the business to automate the credit card routing via a predictive model. Such a model should increase the payment success rate by finding the best possible PSP for each transaction and at the same time keep the transaction fees low. Data Set: The data set and all relevant information from the business side (name of PSPs, transaction fees) are given in a separate *.zip folder, which is available in myCampus, under the section Case Study.
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Data Gathering :
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Data Cleaning : Removed the Duplicates in the data and handled null values in the data.
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Data Preparation : Created new business faturesd based on the data analysis and the features.
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Modelling : Used Logistic Regression, Decision tree, Random Forest, XGBoost models
-Why These multiple models?
Answer) Usually, we try simple model to complex model and look the metrics for understanding right model. -
Deployment
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maintainence.