DeepEP: a deep learning framework for identifying essential proteins

BMC Bioinformatics

Table 1 Performance of DeepEP and other shallow machine learning–based methods with different ratios

Machine learning algorithms	Accuracy	Precision	Recall	F-measure	AUC
SVM (raw dataset)	0.809	0.71	0.12	0.21	0.72
SVM (1:1)	0.813	0.75	0.14	0.23	0.75
Decision tree (raw dataset)	0.698	0.31	0.39	0.35	0.58
Decision tree (1:1)	0.781	0.47	0.54	0.50	0.69
Random forest (raw dataset)	0.809	0.63	0.17	0.27	0.70
Random forest (1:1)	0.843	0.74	0.31	0.43	0.78
Adaboost (raw dataset)	0.805	0.54	0.34	0.42	0.73
Adaboost (1:1)	0.785	0.47	0.39	0.43	0.75
Naïve Bayes (raw dataset)	0.750	0.40	0.44	0.42	0.70
Naïve Bayes (1:1)	0.773	0.41	0.46	0.44	0.71
DeepEP	0.826	0.58	0.52	0.55	0.82

ISSN: 1471-2105