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This repository shows the comparative analysis of different supervised algorithms (DT, LR, RF) in credit card fraud detection. This is a collaborative work to study the effectiveness of supervised learning models in detecting fraudulent activities in context with credit card. Collaborators: (Mr. Anuj Shrestha* (Main) and Ms. Shreyeska Silwal)

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Fraud-Detection-with-WOEencoding

This repository shows the comparative analysis of different supervised algorithms (DT, LR, RF) in credit card fraud detection. This is a collaborative work to study the effectiveness of supervised learning models in detecting fraudulent activities in context with credit card. Collaborators: (Mr. Anuj Shrestha* (Main) and Ms. Shreyeska Silwal)

Data

Download both the training and testing data from url; "https://www.kaggle.com/datasets/kartik2112/fraud-detection/data" fraudTrain.csv fraudTest.csv

References

Bhaskar Boruah (https://www.kaggle.com/bhaskarboruah) Kartik Shenoy (https://www.kaggle.com/kartik2112)

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This repository shows the comparative analysis of different supervised algorithms (DT, LR, RF) in credit card fraud detection. This is a collaborative work to study the effectiveness of supervised learning models in detecting fraudulent activities in context with credit card. Collaborators: (Mr. Anuj Shrestha* (Main) and Ms. Shreyeska Silwal)

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