Table 3.

Comparison of Classification Results on the Vehicle Dataset.

Algorithm	Accuracy	Precision	Recall	F1	AUC	Error
PSOPD-AdaBoost-A	0.925000	0.809345	0.902400	0.851406	0.917187	0.074999
G-AdaBoost	0.923584	0.861940	0.811999	0.833173	0.885012	0.076415
D-AdaBoost	0.924529	0.857178	0.824000	0.836553	0.889777	0.075471
B-AdaBoost	0.914150	0.781936	0.892000	0.831131	0.906493	0.085849
Random Forest	0.911886	0.841605	0.806001	0.823128	0.872567	0.088114
Extra Trees	0.920377	0.831528	0.84800	0.838903	0.896098	0.079633
Smote	0.897169	0.708473	0.960000	0.814594	0.898271	0.102831