This paper is published in Volume-4, Issue-3, 2018
Area
Machine Learning
Author
Sai Kiran
Co-authors
Jyoti Guru, Rishabh Kumar, Naveen Kumar, Deepak Katariya, Maheshwar Sharma
Org/Univ
Bharati Vidyapeeth'S College of Engineering, Paschim Vihar, Delhi, India
Pub. Date
01 May, 2018
Paper ID
V4I3-1165
Publisher
Keywords
Credit card, Fraud detection, Machine learning, Naïve Bayes, Kth nearest neighbor.

Citationsacebook

IEEE
Sai Kiran, Jyoti Guru, Rishabh Kumar, Naveen Kumar, Deepak Katariya, Maheshwar Sharma. Credit card fraud detection using Naïve Bayes model based and KNN classifier, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sai Kiran, Jyoti Guru, Rishabh Kumar, Naveen Kumar, Deepak Katariya, Maheshwar Sharma (2018). Credit card fraud detection using Naïve Bayes model based and KNN classifier. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.

MLA
Sai Kiran, Jyoti Guru, Rishabh Kumar, Naveen Kumar, Deepak Katariya, Maheshwar Sharma. "Credit card fraud detection using Naïve Bayes model based and KNN classifier." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.

Abstract

Machine Learning is the technology, in which algorithms which are capable of learning from previous cases and past experiences are designed. It is implemented using various algorithms which reiterate over the same data repeatedly to analyze the pattern of data. The techniques of data mining are no far behind and are widely used to extract data from large databases to discover some patterns making decisions. This paper presents the Naïve Bayes improved K-Nearest Neighbor method (NBKNN) for Fraud Detection of Credit Card. Experimental results illustrate that both classifiers work differently for the same dataset. The purpose is to enhance the accuracy and enhance the flexibility of the algorithm.
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