Fig. 2
From: Tumor classification and biomarker discovery based on the 5’isomiR expression level
Analysis of GA/SVM-derived optimal feature sets for 100 runs generated by GA/SVM. a The average sensitivity for 100 generated predictor sets. b The average MCC (Matthew’s Correlation Coefficient) for 100 generated predictor sets [43]. c The prediction accuracies for 32 tumor classifications. d The average sensitivity of test-set samples predicted to be each of the 32 tumor types. X-axis and Y-axis list the actual and the predicted cancer type, respectively. The color of each cell in the heatmap is the average sensitivity of the test-set samples originally as the cancer type in X-axis to be predicted as the cancer type in Y-axis