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Table 5 Bioinformatics scenario: binary classification of colon tissue gene expression

From: The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

Rank Method MCC BA BM MK TPR TNR PPV NPV
  MCC ranking:
1 Decision Tree 0.447 0.715 0.429 0.477 0.728 0.701 0.774 0.702
2 Radial SVM 0.423 0.695 0.390 0.517 0.891 0.498 0.754 0.726
3 k-Nearest Neighbors 0.418 0.706 0.412 0.443 0.887 0.525 0.826 0.617
4 Naïve Bayes 0.408 0.722 0.444 0.375 0.778 0.667 0.875 0.500
  BA ranking:
1 Naïve Bayes 0.408 0.722 0.444 0.375 0.778 0.667 0.875 0.500
2 Decision Tree 0.447 0.715 0.429 0.477 0.728 0.701 0.774 0.702
3 k-Nearest Neighbors 0.418 0.706 0.412 0.443 0.887 0.525 0.826 0.617
4 Radial SVM 0.423 0.695 0.390 0.517 0.891 0.498 0.754 0.726
  BM ranking:
1 Naïve Bayes 0.408 0.722 0.444 0.375 0.778 0.667 0.875 0.500
2 Decision Tree 0.447 0.715 0.429 0.477 0.728 0.701 0.774 0.702
3 k-Nearest Neighbors 0.418 0.706 0.412 0.443 0.887 0.525 0.826 0.617
4 Radial SVM 0.423 0.695 0.390 0.517 0.891 0.498 0.754 0.726
  MK ranking:
1 Radial SVM 0.423 0.695 0.390 0.517 0.891 0.498 0.754 0.726
2 Decision Tree 0.447 0.715 0.429 0.477 0.728 0.701 0.774 0.702
3 k-Nearest Neighbors 0.418 0.706 0.412 0.443 0.887 0.525 0.826 0.617
4 Naïve Bayes 0.408 0.722 0.444 0.375 0.778 0.667 0.875 0.500
  1. Radial SVM: Support Vector Machine with radial Gaussian kernel. Positives: patients diagnosed with colon cancer. Negatives: healthy controls. MCC: Matthews correlation coefficient(Eq. 5). BA: balanced accuracy (Eq. 6). BM: bookmaker informedness (Eq. 7). MK: markedness (Eq. 8). TPR: true positive rate. TNR: true negative rate. PPV: positive predictive value. NPV: negative predictive value. MCC, BM, MK value interval: [−1,+1]. BA, TPR, TNR, PPV, NPV value interval: [0,1].
  2. Bold values represent the corresponding ranking for each metric
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