Performance of support-vector-machine-based classification on 15 systematic review topics evaluated with the WSS@95 measure: Table 1

Abstract

In the July 2010 issue of JAMIA, Matwin et al published an article entitled ‘A new algorithm for reducing the workload of experts in performing systematic reviews.’1 Briefly, the work proposes a factorized variant of the complement Naïve Bayes classifier as an improvement, using weight engineering on the features (FCNB/WE). The prior work of Cohen et al in this area is cited, and the data set made public along with this prior work is used for the evaluation.2