Improved Pre-miRNA Classification by Reducing the Effect of Class Imbalance

Table 7

The classification results of MiRNAClassify and three classification models over the merged datasets.

Classification models	SE (%)	SP (%)	(%)
Human
SVM	69.18	99.83	83.11
SVM + SMOTE	92.25	95.70	93.96
Naive Bayes	87.43	96.12	91.67
Naive Bayes + SMOTE	90.24	94.43	92.31
Random Forest	67.78	99.82	82.26
Random Forest + SMOTE	91.51	95.34	93.41
MiRNAClassify	97.93	98.30	98.11
Animal
SVM	69.03	98.14	82.31
SVM + SMOTE	91.61	94.85	93.21
Naive Bayes	85.04	95.03	89.90
Naive Bayes + SMOTE	90.83	92.61	91.71
Random Forest	69.52	98.72	82.84
Random Forest + SMOTE	91.12	95.01	93.05
MiRNAClassify	95.85	97.62	96.73
Plant
SVM	68.51	99.24	82.45
SVM + SMOTE	89.50	93.10	91.28
Naive Bayes	82.91	96.75	89.57
Naive Bayes + SMOTE	87.20	92.61	89.86
Random Forest	68.32	99.35	82.39
Random Forest + SMOTE	89.18	92.87	91.01
MiRNAClassify	93.37	97.91	95.61