afterdusk / cs3244-fraud-detection

Class imbalance and supervised learning methods in fraud detection

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cs3244-fraud-detection

CS3244 Machine Learning AY18/19 Sem 1 Project
Project Members: Alvin Yan, Dexter Wah, Joycelyn Ng, Kenny Ng, Liew Jia Hong, Au Liang Jun
This study explored resampling techniques and ensembling via model stacking on top of traditional supervised learning methods. On top of general contributions, I was responsible for the model stacking related components, researching the topic, verifying implementation and writing explanations/creating diagrams.

Video: https://youtu.be/XeyjLNjLvJs
Dataset: https://www.kaggle.com/mlg-ulb/creditcardfraud

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Class imbalance and supervised learning methods in fraud detection


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