Enhanced accuracy performance in detecting phishing website based on neuro fuzzy scheme comparison with support vector machine algorithm.

This study primarily employs a support vector machine strategy and a novel neuro fuzzy scheme to address the issue of cyberattacks on online content. After using the proposed approaches, we get an 80% G-power after estimating 10 samples for each group. When comparing the two algorithms, it is remarkable to see that the Support Vector Machine Algorithm outperforms the neuro fuzzy algorithm by an incredible 85 percent when it comes to identifying phishing websites. In SPSS's view, the two datasets couldn't be more different. The data indicates that a significance level of 0.001 (p<0.05) is necessary. In this study, the Support Vector Machine Algorithm outperformed neuro fuzzy systems in predicting retinopathy. [ABSTRACT FROM AUTHOR]