[Retracted] Predicting the Growth of F. proliferatum and F. culmorum and the Growth of Mycotoxin Using Machine Learning Approach

Table 1

Performance of ML models for predicting the growth rate, HR-2, and T-2.

Output parameter	Machine learning tested model	Parameter of best model
Growth rate	XGBoost	; , , , , , ,	1.445	0.866
	Artificial neural network		1.265	0.898
	SVM		1.162	0.921
	Random forest		1.542	0.918
	MLR		1.670	0.845
Production of T-2	XGBoost	; , , , , , ,	0.768	0.795
	Artificial neural network		0.402	0.945
	SVM		0.356	0.765
	Random forest		0.623	0.787
	MLR		0.635	0.765
Production of HT-2	XGBoost	; , , , , , ,	0.543	0.723
	Artificial neural network		0.525	0.782
	SVM		0.567	0.805
	Random forest		0.543	0.775
	MLR		0.885	0.764