Table 2. Results of the performance metrics of various neural network configurations and classification models.

Complete model with 23 variables
Hidden Layers	Internal configuration (number of hidden neurons)	Accuracy	Precision
1	10	0.975	0.97
2	(10, 15)	0.9625	0.97
3	(10, 15, 15)	0.9375	0.95
4	(10, 15, 15, 25)	0.9375	0.94
Logistic regression		0,875	0.9563
Support vector machines		0.8625	0.9531
Nearest neighbor		0.7875	0.8719
Decision trees		0.8125	0.8100
Model reduced to 18 variables
Hidden Layers	Internal configuration (number of hidden neurons)	Accuracy	Precision
1	20	0.975	0.98
2	(20, 25)	0.95	0.95
3	(20, 25, 25)	0.9375	0.92
4	(20, 25, 25, 20)	0.85	0.79
Logistic regression		0,925	0.9467
Support vector machines		0.85	0.8844
Nearest neighbor		0,825	0.8594
Decision trees		0.8578	0.8650