Table 3.

Validation results of various classification models before and after data fusion.

Validation Metrics	Before Fusion					After Fusion
	LR	SVC	DT	eRF	GN	LR	SVC	DT	eRF	GN
Training Accuracy	0.5629	0.5931	0.6252	0.7641	0.6056	0.6486	0.6225	0.8642	0.9513	0.7631
Test Accuracy	0.5933	0.6381	0.6473	0.6986	0.6267	0.7102	0.6814	0.7928	0.9168	0.8025
Precision	0.6267	0.6179	0.7019	0.7327	0.6539	0.6963	0.7015	0.8239	0.8821	0.8323
Recall	0.5898	0.7073	0.7263	0.7705	0.6822	0.6687	0.7432	0.8512	0.8975	0.7516
RMSE	0.4912	0.4536	0.5498	0.4132	0.4226	0.4372	0.3643	0.4758	0.3481	0.3529
MAE	0.3425	0.3503	0.2978	0.2315	0.2931	0.2763	0.2307	0.2582	0.2096	0.2459