Fraudulent Detection in Credit Card System Using SVM & Decision Tree
Vijayshree Bhaskar Nipane
, Poonam S. Kalinge , Dipali Vidhate , Kunal War , Bhagyashree P. Deshpande
SVM; Decision Tree; Model File; Prediction File; Libsvmtools; LIBSVM; fraudster;
With growing advancement in the electronic commerce field, fraud is spreading all over the world, causing major financial losses. In current sce-nario, Major cause of financial losses is credit card fraud; it not only affects tra-des person but also individual clients. Decision tree, Genetic algorithm, Meta learning strategy, neural network, HMM are the presented methods use to detect credit card frauds. In contemp-late system for fraudulent detection, artificial intelligence concept of Support Vector Machine (SVM) & decision tree is being used to solve the problem. Thus by implementation of this hybrid approach, financial losses can be reduced to greater extend.
"Fraudulent Detection in Credit Card System Using SVM & Decision Tree", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 5, page no.590 - 594, May-2016, Available :https://ijsdr.org/papers/IJSDR1605113.pdf
Volume 1
Issue 5,
May-2016
Pages : 590 - 594
Paper Reg. ID: IJSDR_160368
Published Paper Id: IJSDR1605113
Downloads: 000347077
Research Area: Engineering
Country: Jalgaon, maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
