A Repo of my solution to the Bootcamp Qualification competition 5th Place Solutuion
Position on Leader Board -- 5th of 750 (Top 1%)
link -- https://zindi.africa/hackathons/dsn-ai-bootcamp-qualification-hackathon
Kowope Mart is a Nigerian-based retail company with a vision to provide quality goods,education and automobile services to its customer at affordable price and reduce if not eradicate charges on card payments and increase customer satisfaction with credit rewards that can be used within the Mall. To achieve this the company has partnered with DSBank on co-branded credit card with additional functionality such that customers can request for loan, pay for goods even with zero-balance and then pay back within an agreed period of time. This innovative strategy has increased sales for the company. However, there has been recent cases of credit defaults and Kowope Mart will like to have a system that profiles customers who are worthy of the card with minimum if not zero risk of defaulting.
You have been employed as a Data Scientist to leverage Machine Learning to predict customers who are likely to default or not.
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A Catboost Model
- Created Cluster with the Best four features
- Used a Kfold of 7 Splits
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Voting Classifier of Catboost and Lgbm
- Engineered new Feature
- Used feature Interaction
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Voting Classifer of Tree Based Model
- Engineered new Feature
- Used feature Interaction
- Used a Kfold of 10 Splits
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Finally created a Blend Model for the Tree Model
- Better Feature Engineering
- Domain Knowledge would proved better
- Magic Features
- Hyper Parameter Tunning: I used a cpu all through so could not do much on that
- Feature Interaction
- Feature Selection