Aim: The principle objective of this article is to improve the accuracy of Credit card fraud detection using Novel logistic regression compared with the t-SNE. Materials and Methods: The categorizing is performed by adopting a sample size of n = 10 in novel logistic regression and sample size n = 10 in t-SNE with a sample size = 10, obtained using the G-power value 80%. Results: The analysis of the results shows that the Novel logistic regression has a high accuracy of (99.89) in comparison with the t-SNE(60.99). There is a statistically significant difference between the study groups with (p< 0.05). Conclusion: For Credit card fraud detection it shows that the Logistic Regression appears to generate more accuracy than the t-SNE
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.