Credit Card Fraud Detection using Decision Tree and Random Forest
Dhwanir Shah, Lokesh Kumar Sharma
Abstract
It is the time of technology advancement. Due to internet everything is available at the touch of a finger. There is a benefit of online shopping: first it saves lots of time and second it does not demand to go to market to buy anything. There exists various mode of payments and credit card payment is one of them. Today, there exists a good number of credit card users in the world. Every day so many credit cards transactions are taken place. Some of these transactions are fraudulent. Due to such fraudulent transactions banks and customers need to suffer. In order to prevent financial losses due to credit card fraud, a secure credit card fraud detection system is essential. Various machine learning algorithms like Naïve Bayes, Logistic regression, SVM, Decision trees, Random Forest, Genetic algorithm, J48 and AdaBoost, etc. are used for credit card fraud detection. The motive of this paper is to provide some insight about the credit card fraud along with the analysis of the dataset and also Decision tree and random forest algorithms are going to be discussed.