In our experiments, we used cost matrices of size 2x2 where the main diagonal of the cost matrices was fixed as C(0; 0) = C(1; 1) = 0, the misclassification cost for each object of the majority class is C(0; 1) = 1, while for the misclassification cost for objects of the minority we use C(0; 1) = 2; 5; 10; 20 and the class imbalance ratio (IR) of the training database.
|Actual minority||Actual Majority|
|Predict Minority||C(0, 0) = 0||C(0, 1) = 1|
|Predict Majority||C(1, 0) = 2, 5, 10, 20, or IR||C(1, 1) = 0|
Statistical results using Friedman's test (as a non-parametric test) and Finner's procedure (as a post-hoc procedure) . The post hoc comparisons contain α = 0.05 and adjusted p-values.
CSPm+CACSP algorithm was implemented on .NET environment. In the CSPmCACSP.zip file we provide the source code of the CSPm+CACSP algorithm and some examples using ARFF (WEKA database file) and COST (WEKA costmatrix file) files->
 J. Derrac, S. García, D. Molina, and F. Herrera, “A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,” Swarm Evol. Comput., vol. 1, no. 1, pp. 3–18, 2011.