Credit Card Fraud Detection Using Logistic Regression and Machine Learning Algorithms
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Credit Card Fraud Detection Using Logistic Regression and Machine Learning Algorithms

Abstract

This thesis is focused on detecting the probability of credit card fraud occurrence according to seven relative independent variables by using logistic regression, support vector machine, decision tree, and k-NN models. The dataset provided by Dhanush Narayanan R from Kaggle contains one million of data [1]. The final goal is to compare these four models and find the most accurate model.

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