Figure 1

Results of the performance evaluation of various classification algorithms and their resultant models tested in our framework, grouped by several evaluation measures (A): High-risk class; (B): Lower-risk class). Also shown are the results of the statistical comparison of these performances in the form of Critical Difference (CD) plots for the high (C) and lower (D) PCa risk classes respectively. Classification algorithms, represented by vertical + horizontal lines, are displayed from left to right in terms of the average rank obtained by their resultant models in each of the ten cross-validation rounds, and the classifiers producing statistically equivalent performance are connected by horizontal lines. These results show that the Quadratic kernel-based SVM (QSVM) is the best performer overall, especially because it is the only classifier that is statistically the best performer (leftmost classifier in the plots, either by itself or tied with another classifier like CSVM or LogReg) in terms of all the evaluation measures for both the classes. The CD plots were drawn using open-source Matlab code.