Table 5.

Evaluation results of Diabetes dataset using different sampling strategies with three metrics across ten classification algorithms.

Method	Metric	Classifier
		J48	3NN	NB	RF5	LOG	1NN	7NN	SMO	RF10	RBFNet	R. Avg.
PSO	AUC	0.746	0.761	0.808	0.801	0.827	0.693	0.793	0.740	0.817	0.786	0.777
	FMeasure	0.660	0.618	0.638	0.662	0.661	0.612	0.651	0.662	0.671	0.639	0.647
	GMean	0.734	0.698	0.717	0.736	0.734	0.691	0.727	0.738	0.745	0.719	0.724
	C. Avg.	0.713	0.692	0.721	0.733	0.741	0.665	0.724	0.713	0.744	0.715	0.716
RU	AUC	0.697	0.739	0.801	0.765	0.829	0.665	0.773	0.737	0.791	0.759	0.756
	FMeasure	0.635	0.603	0.635	0.628	0.665	0.581	0.636	0.657	0.659	0.609	0.631
	GMean	0.707	0.686	0.714	0.705	0.740	0.660	0.714	0.734	0.734	0.694	0.709
	C. Avg.	0.680	0.676	0.717	0.699	0.745	0.635	0.708	0.709	0.728	0.687	0.699
RO	AUC	0.709	0.722	0.799	0.774	0.831	0.653	0.774	0.735	0.796	0.797	0.760
	FMeasure	0.634	0.592	0.628	0.612	0.665	0.549	0.621	0.656	0.616	0.636	0.622
	GMean	0.713	0.675	0.705	0.696	0.739	0.643	0.699	0.733	0.696	0.716	0.702
	C. Avg.	0.685	0.663	0.711	0.694	0.745	0.615	0.698	0.708	0.703	0.716	0.695
Cluster	AUC	0.701	0.729	0.801	0.759	0.813	0.608	0.769	0.753	0.788	0.784	0.751
	FMeasure	0.624	0.603	0.635	0.598	0.684	0.513	0.626	0.680	0.643	0.629	0.624
	GMean	0.702	0.678	0.711	0.686	0.723	0.615	0.698	0.752	0.721	0.711	0.700
	C. Avg.	0.676	0.670	0.716	0.681	0.740	0.579	0.698	0.728	0.717	0.708	0.692