Table 4.

Comparing the performance of diverse classifiers.

Feature	Classifier	Pre	Rec	F	Feature	Classifier	Pre	Rec	F
Degree	NB	0.714	0.227	0.345	EC	NB	0.719	0.162	0.264
	SMO	0.686	0.150	0.246		SMO	0.736	0.127	0.216
	J48	0.667	0.598	0.631		J48	0.653	0.509	0.572
	LMT	0.667	0.598	0.631		LMT	0.634	0.546	0.587
	RF	0.661	0.576	0.615		RF	0.533	0.522	0.528
	RT	0.664	0.586	0.623		RT	0.531	0.524	0.528
	REPT	0.658	0.599	0.627		REPT	0.629	0.543	0.583
	NC	0.667	0.598	0.631		NC	0.660	0.401	0.499
SC	NB	0.670	0.054	0.100	PeC	NB	0.810	0.244	0.375
	SMO	0.714	0.017	0.033		SMO	0.846	0.175	0.290
	J48	0.655	0.513	0.575		J48	0.759	0.295	0.425
	LMT	0.638	0.542	0.586		LMT	0.682	0.402	0.506
	RF	0.532	0.530	0.531		RF	0.542	0.538	0.540
	RT	0.529	0.532	0.531		RT	0.541	0.538	0.540
	REPT	0.618	0.559	0.587		REPT	0.660	0.402	0.499
	NC	0.665	0.376	0.481		NC	0.747	0.341	0.468
ION	NB	0.722	0.638	0.678	Modules	NB	0.715	0.530	0.609
	SMO	0.715	0.663	0.688		SMO	0.715	0.530	0.609
	J48	0.711	0.626	0.665		J48	0.715	0.530	0.609
	LMT	0.707	0.679	0.692		LMT	0.715	0.530	0.609
	RF	0.662	0.568	0.611		RF	0.715	0.530	0.609
	RT	0.659	0.584	0.619		RT	0.715	0.530	0.609
	REPT	0.708	0.638	0.671		REPT	0.715	0.530	0.609
	NC	0.717	0.655	0.684		NC	0.715	0.530	0.609
Nucleus	NB	0.654	0.638	0.646	UDoNC	NB	0.828	0.226	0.355
	SMO	0.654	0.638	0.646		SMO	0.902	0.039	0.076
	J48	0.654	0.638	0.646		J48	0.722	0.544	0.620
	LMT	0.654	0.638	0.646		LMT	0.716	0.553	0.624
	RF	0.654	0.638	0.646		RF	0.693	0.693	0.577
	RT	0.654	0.638	0.646		RT	0.689	0.495	0.576
	REPT	0.654	0.638	0.646		REPT	0.690	0.589	0.636
	NC	0.654	0.638	0.646		NC	0.759	0.459	0.572
Feature subset	NB	0.807	0.380	0.516
	SMO	0.740	0.710	0.725
	J48	0.728	0.717	0.722
	LMT	0.736	0.723	0.729
	RF	0.710	0.729	0.720
	RT	0.644	0.661	0.652
	REPT	0.705	0.689	0.697
	NC	0.745	0.715	0.730