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.
Dimensionality Reduction Algorithms
Gradient Boosting algorithms
Name,Type,Amount,Where Issued,Where Used,Age,IsFradulent
Skills & Expertise RequiredMachine Learning
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