Journal of Engineering and Applied Science

Table 3 Machine learning and deep learning model fit error statistical and evaluation metrics

From: Machine learning algorithm and neural network architecture for optimization of pharmaceutical and drug manufacturing industrial effluent treatment using activated carbon derived from breadfruit (Treculia africana)

	SVM	MLR	RFM	DTM	ANN	CNN	LSTM
MAE	0.8084	0.8080	0.7601	0.7692	0.7957	0.9142	0.9373
MSE	1.1612	1.1519	1.0272	1.0616	1.2732	1.6813	1.2905
RMSE	1.0776	1.0733	1.0135	1.0303	1.1283	1.2966	1.1360
Predicted R²	0.9401	0.9406	0.9411	0.9391	0.9269	0.9035	0.9335
Mean ave	0.8084	0.8080	0.7601	0.7692	0.7952	0.9243	0.9448
Std. dev	1.0776	1.0733	1.0109	1.0286	1.1181	1.3086	1.0596

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