Efficient Predictive System for the Detection of Brain Tumor Using Naive Bayes Algorithm Compared with Support Vector Machine Algorithm

The research focuses on improving the prediction system for detecting brain tumors by using the Naive Bayes algorithm. This method has proven to be more accurate com- pared to the Support Vector Machines (SVM). The study used a sample size of 10 for both the Naive Bayes and SVM algorithms to classify brain tumor data. The results show that the Naive Bayes algorithm achieved an impressive accuracy rate of 92.36%, significantly higher than the 55.26% accuracy of the Support Vector Machines. This difference is statistically significant with a p-value of less than 0.001, indicating that the Naive Bayes algorithm performs better in detecting brain tumors.