Knowledge Reduction Based on Divide and Conquer Method in Rough Set Theory

Table 8

The experimental results of 3 algorithms on KDDCUP99 data sets (≤10⁶ records).

Number of records	C4.5			CART			Our methods
	RRate	Tr	Te	RRate	Tr	Te	RRate	Tr	Te
100000	0.9992	18730	31	0.9991	56208	8	0.9992	51692	24
200000	0.9997	52971	32	0.9994	113297	8	0.9995	113496	16
300000	0.9997	78118	47	0.9997	182997	0	0.9997	178769	31
400000	0.9998	111026	86	0.9997	327640	23	0.9997	313085	40
500000	0.9997	163746	94	0.9998	391179	16	0.9997	410342	55
600000	0.9998	218152	110	0.9996	446004	16	0.9997	538169	55
700000	0.9998	226879	125	0.9997	610749	24	0.9998	719630	78
800000	0.9999	387911	148	0.9999	1015165	32	0.9999	1143149	109
900000	0.9998	304466	195	0.9999	1595899	382	0.9998	1512619	133
1000000	0.9999	303403	203	0.9997	1583910	367	0.9998	1590494	140