• Murugavel.P
• Akash.S,Adithyan.R
• S.Niveditha
• Mrs.M.Poonkodi

Due to increase of fraud which results in loss of money across the globe, several methodologies and techniques developed for detecting frauds Fraud detection involves analyzing the activities of users in order to understand the malicious behaviour of users. Malicious behaviour is a broad term including delinquency, fraud, intrusion, and account defaulting. This paper presents a survey of current techniques used in credit card fraud detection and evaluates the machine learning approach to identify fraud detection. In the proposed work, we analyze credit card fraud detection using machine learning algorithm namely K-Nearest Neighbor and Ensemble Model of Random Forest. To make the learning process efficient, we used infinite latent feature selection algorithm for feature selection. The performance of the algorithm is evaluated on various measures like Accuracy, Precision and Recall.

Machine learning, Ensemble Model of Random Forest, KNN.

"Credit Card Fraud detection using Machine Learning Models ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.104-110, May-2020, Available :http://www.jetir.org/papers/JETIRDV06024.pdf

"Credit Card Fraud detection using Machine Learning Models ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp104-110, May-2020, Available at : http://www.jetir.org/papers/JETIRDV06024.pdf