Determining the accuracy in purifying unsolicited electronic message using novel random forest algorithm comparing support vector machine algorithm.

Determining the research goal is to categorize unsolicited electronic messages via the use of a comparison of the RF Algorithm and the SVM Algorithm for purifying junk messages. To determine accuracy percentage, Random Forest and Support Vector Machine algorithms with sample sizes of 10 were analyzed repeatedly with G power values of 0.8 and 0.8, respectively. When comparing the RF Algorithm's accuracy (88.890%) to the SVM Algorithm's accuracy (77.990%), the results reveal that the former produces better outcomes. The significance value of the two-tailed test is 0.001, and p-value of 0.001 (p<0.05) indicates that the difference between the two algorithms is statistically significant. [ABSTRACT FROM AUTHOR]