Table 2.

UCI datasets and their features: number of attributes (#A), number of samples (#S), and number of classes (#C).

Dataset	Acronym	#A	#S	#C	Brief description
BREAST	BR	9	699	2	For breast tumor diagnosis
HEART	HE	13	303	2	For detecting heart disease; the “goal” field refers to the presence of heart disease in the patient
PIMA	PI	8	768	2	For forecasting the onset of diabetes mellitus
Spam	SP	57	4601	2	For classifying E-mail as spam or nonspam
SONAR	SO	60	208	2	For discriminating between sonar signals bounced off a metal cylinder and those bounced off a rough cylindrical rock
IONOSPHERE	IO	34	351	2	For classifying radar returns from the ionosphere
Liver	LI	7	345	2	For classifying liver disorders that might arise from excessive alcohol consumption
Haberman	HA	3	306	2	A dataset that contains cases on the survival of patients who had undergone surgery for breast cancer
Vote	VO	16	435	2	For classifying Republican versus Democrat US representatives (this dataset includes votes for each member of the US House of Representatives on 16 key votes)
Australian	AU	14	690	2	For credit card applications
Transfusion	TR	5	748	2	This study adopted the donor database of Blood Transfusion Service Center; the aim is to predict whether a person donated blood in March, 2007