Credit Card Fraud Detection - Case Study School Project




Charles New Zealand


OpenAug 22, 2018
I have sample transaction records that are manually classified as either 'fraudulent' or 'non-fraudulent'.

I want to use these records to train a supervised machine learning algorithm.

After building a model using this training data, the algorithm should be able to classify new records as either fraudulent or non-fraudulent.

Please let me know which of the following algorithms you can leverage to accomplish said task and what software you'll use.

Linear Regression
Logistic Regression
Decision Tree
Naive Bayes
Random Forest
Dimensionality Reduction Algorithms
Gradient Boosting algorithms

Example Records:
Name,Type,Amount,Where Issued,Where Used,Age,IsFradulent

Thank you!

Skills & Expertise Required

Machine Learning 

Offer to work on this project closes in 29 days!

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