• K. Nageswarao
• P.N.V Vamsi Lala
• Jattiboyina Hemalatha
• Kanaparthi Anoohya
• Narne Vyshnavi, Pulivarthi Srividya, Singamsetty Srilatha

The today's world is driven by innovation, science and inventive measures making numerous ordinary errands much less complex for the people. One such occurrence where innovation comes convenient is utilization of installment cards and online exchanges. Installment cards give a straightforward and helpful strategy for making buys. Be that as it may, owing to the increment within the utilization of installment cards, particularly in online buys, extortion cases are on the rise. Within the later times, the e-payments have driven to an increment in monetary extortion cases such as credit card fakes. Subsequently, numerous companies have begun utilizing machine learning calculations to create models that are utilized for credit card extortion discovery. A few procedures utilized are Back Vector Machine, Calculated Relapse, Irregular Timberland and their blends. In this comparative think about, the proposed credit card extortion discovery is performed on a dataset of different card holders. The results emphatically point towards the viability of utilizing amassed highlights for undertaking real-world installment card extortion location issues. Catchphrases: Machine learning; Extortion discovery; Prescient modeling; Calculated Relapse

CREDIT CARD FRAUD DETECTION USING RANDOM FOREST ALGORITHM

"CREDIT CARD FRAUD DETECTION USING RANDOM FOREST ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.65-75, November-2024, Available :http://www.jetir.org/papers/JETIRGO06007.pdf

"CREDIT CARD FRAUD DETECTION USING RANDOM FOREST ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp65-75, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06007.pdf