tejdeep94 / EE769-Project

Evaluating the performance of classifiers in a fraud detection application

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Tejdeep Reddy - 173230004, Arijit Sarkar - 173230014

Project Title: Evaluating the performance of classifiers in a fraud detection application on computer networks

This contains separate folders for PCA, LDA and a combination PCA & LDA methods used for feature engineering. Each of the folders has a train file, test file, trained models of Neural Networks and Decision Tree classifiers. KTrain+ and KTest+ are the datasets taken as input. These are obtained from the NSL-KDD dataset. Note: These datasets need to be in the same path of every train and test codes that are going to be run.

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Evaluating the performance of classifiers in a fraud detection application


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