Direct comparison between support vector machine and multinomial naive Bayes algorithms for medical abstract classification
Stan Matwin, Vera Sazonova · Journal of the American Medical Informatics Association · 2012
In 2011 Matwin et al published a letter to JAMIA entitled ‘Performance of SVM and Bayesian classifiers on the systematic review classification task’.1 This letter continued a discussion on the relative benefits of using support vector machine (SVM) and Bayesian techniques for performing systematic reviews.2–4 In particular, it was suggested that the running time of algorithms must be taken into consideration when comparing their performances as it becomes very important for large datasets. Following up on this idea, we attempted to directly compare the performance of a Bayesian method with the SVM algorithm used by Cohen in his original work.4 The same SVM system (SVMlight5) with the same parameters as was …