Table 5. Metrics recall (Benchmark techniques VS MLEn).

Methods/Datasets	Automobiles (%)	Birds (%)	Emotions (%)	Hotel (%)	Medical (%)	Movies (%)	News (%)	Proteins (%)
DenseNet-EHO	0.94	0.92	0.95	0.93	0.96	0.94	0.92	0.95
BERT [52]	0.87	0.90	0.88	0.86	0.89	0.87	0.90	0.90
ML-RBF [30]	0.78	0.76	0.79	0.77	0.8	0.78	0.76	0.79
RAKEL [9]	0.82	0.8	0.83	0.81	0.84	0.82	0.8	0.83
ECC [31]	0.75	0.73	0.76	0.74	0.77	0.75	0.73	0.76
CNN [5]	0.8	0.78	0.81	0.79	0.82	0.8	0.78	0.81
NB [6]	0.76	0.74	0.77	0.75	0.78	0.76	0.74	0.77
LSTM [32]	0.83	0.8	0.84	0.82	0.85	0.83	0.8	0.84
ResNet [14]	0.85	0.82	0.86	0.84	0.87	0.85	0.82	0.86
CapsNet [33]	0.82	0.79	0.83	0.81	0.84	0.82	0.79	0.83
GRU [51]	0.79	0.76	0.80	0.78	0.81	0.79	0.76	0.80