Result for “ A voting approach to identify small number of highly predictive genes based on multiple classifiers ”

• C4.5 can achieve an average of 88.49% accuracy using at most from 1 to 4 genes for different fold. While in the test set the same classifier used only one gene to achieve a maximum accuracy of 84.52%. • C4.5 with boosting can achieve an average of 89.54% accuracy using at most from 1 to 5 genes for different fold. While in the test set the same classifier used 4 genes to achieve a maximum accuracy of 91.67%. • C4.5 with bagging can achieve an average of 88.94% accuracy using at most from 1 to 6 genes for different fold. While in the test set the same classifier used only one gene to achieve a maximum accuracy of 84.52%. • Naive Bayes can achieve an average of 84.52% accuracy using at most from 1 to 6 genes for different fold. While in the test set the same classifier used only one gene to achieve a maximum accuracy of 84.52%. • Naive Bayes with bagging can achieve an average of 92.13% accuracy using at most from 1 to 4 genes for different fold. While in the test set the same classifier used 4 genes to achieve a maximum 1