Accurate plant pathogen effector protein classification ab initio with deepredeff: an ensemble of convolutional neural networks

Table 2 Accuracy and loss values from best performing parameters values for each model

Group	Data set	Model	Accuracy	Loss
Bacteria	Training	CNN-LSTM	0.917	0.334
Bacteria	Training	CNN-GRU	0.965	0.148
Bacteria	Training	LSTM-Emb	0.978	0.129
Bacteria	Training	GRU-Emb	0.947	0.202
Bacteria	Validation	CNN-LSTM	0.855	0.377
Bacteria	Validation	CNN-GRU	0.947	0.205
Bacteria	Validation	LSTM-Emb	0.934	0.232
Bacteria	Validation	GRU-Emb	0.895	0.385
Fungi	Training	CNN-LSTM	0.907	0.362
Fungi	Training	CNN-GRU	0.814	0.434
Fungi	Training	LSTM-Emb	0.771	0.505
Fungi	Training	GRU-Emb	0.788	0.484
Fungi	Validation	CNN-LSTM	0.526	0.923
Fungi	Validation	CNN-GRU	0.579	0.799
Fungi	Validation	LSTM-Emb	0.711	0.504
Fungi	Validation	GRU-Emb	0.842	0.468
Oomycete	Training	CNN-LSTM	0.657	0.626
Oomycete	Training	CNN-GRU	0.833	0.429
Oomycete	Training	LSTM-Emb	0.863	0.314
Oomycete	Training	GRU-Emb	0.706	1.487
Oomycete	Validation	CNN-LSTM	0.735	0.761
Oomycete	Validation	CNN-GRU	0.618	0.677
Oomycete	Validation	LSTM-Emb	0.588	0.910
Oomycete	Validation	GRU-Emb	0.500	1.486

ISSN: 1471-2105