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Table 2 Performance metrics for comparison of DeepM6ASeq with other classifiers on the mammalian independent dataset

From: DeepM6ASeq: prediction and characterization of m6A-containing sequences using deep learning

  Accuracy F1-score AUROC AUPR MCC
DeepM6ASeq 0.764 0.762 0.844 0.831 0.528
Random forest 0.747 0.756 0.826 0.809 0.494
Logistic regression 0.743 0.736 0.824 0.807 0.487
Support vector machine 0.736 0.732 0.818 0.802 0.472
  1. The highest value for each accuracy measure is highlighted in bold