Eurasian Journal of Academic Research 4-jild 12-son (2024) · 738–745-betlar

CREDIT CARD FRAUD DETECTION USING MACHINE LEARNING TECHNIQUES

Primbetov, Abbaz, Jumaev, Giyosjon, Normo‘minov, Anvarjon

DOI: 10.5281/zenodo.14807876 · Manbada o'qish →

Annotatsiya

Credit card fraud represents a major issue, resulting in billions of dollars lost annually. Machine learning offers a solution for detecting such fraud by identifying patterns that indicate fraudulent transactions. Credit card fraud encompasses both the physical loss of a credit card and the theft of sensitive credit card information. Various machine learning algorithms can be employed for detection purposes. This project aims to develop a machine learning model specifically designed to identify credit card fraud. The model will be trained on a dataset of historical credit card transactions and evaluated using a separate holdout dataset of unseen transactions.

Credit Card Fraud Detection, Fraud Detection, Fraudulent Transactions, K- Nearest Neighbors, Support Vector Machine, Logistic Regression, Decision Tree.

Metadata manbasi: jurnal OAI-PMH arxivi · Sindex to'liq matnni saqlamaydi, manbaga havola beradi.