Evaluation of text classification using Support Vector Machine compare with Naive Bayes, Random Forest Decision Tree and K-NN

This paper aims to find the boost model which brings the best accuracy in text classification by using Support Vector Machine in comparison with other models namely Naive Bayes, Random Forest Decision Tree and K-NN. For the text classification and processing, the planned system will have to apply with the Support Vector Machine and the result is decided by major roles. Based on the Machine Learning algorithms used for the implementation of the research- the BBC news dataset- illustrates that the Support Vector Machine has better accuracy and result