Table 7.

Evaluation results of AMD-CGA 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	0.609	0.559	0.606	0.591	0.566	0.599	0.590	0.572	0.573	0.540	0.581
	FMeasure	0.481	0.462	0.489	0.464	0.448	0.485	0.468	0.460	0.465	0.455	0.468
	GMean	0.580	0.557	0.572	0.551	0.538	0.576	0.573	0.550	0.545	0.539	0.558
	C. Avg.	0.557	0.526	0.556	0.535	0.517	0.553	0.544	0.527	0.528	0.511	0.536
RU	AUC	0.569	0.547	0.549	0.594	0.567	0.569	0.579	0.556	0.604	0.570	0.570
	FMeasure	0.434	0.457	0.439	0.476	0.453	0.439	0.446	0.417	0.456	0.446	0.446
	GMean	0.538	0.556	0.538	0.580	0.551	0.547	0.553	0.523	0.550	0.549	0.549
	C. Avg.	0.514	0.520	0.509	0.550	0.524	0.518	0.526	0.499	0.537	0.522	0.522
RO	AUC	0.566	0.568	0.565	0.597	0.581	0.569	0.586	0.558	0.576	0.586	0.575
	FMeasure	0.394	0.405	0.375	0.442	0.420	0.415	0.407	0.358	0.421	0.428	0.407
	GMean	0.523	0.530	0.505	0.564	0.544	0.539	0.537	0.490	0.547	0.555	0.533
	C. Avg.	0.494	0.501	0.482	0.534	0.515	0.508	0.510	0.469	0.515	0.523	0.505
Cluster	AUC	0.519	0.595	0.560	0.601	0.580	0.580	0.566	0.545	0.581	0.576	0.570
	FMeasure	0.306	0.343	0.358	0.357	0.332	0.270	0.301	0.368	0.387	0.339	0.445
	GMean	0.499	0.558	0.532	0.566	0.548	0.569	0.546	0.511	0.554	0.548	0.543
	C. Avg.	0.441	0.499	0.483	0.508	0.487	0.473	0.471	0.475	0.507	0.488	0.519