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

Table 2

The recognition of 6 algorithms on uci data sets.

Data sets	KNN	SVM	C4.5	Naive bayes	CART	Our methods
Zoo	0.9208	0.9603	0.8713	0.9702	0.9109	0.9208
Iris	0.9600	0.9467	0.9600	0.9533	0.9533	0.9467
Wine	0.9719	0.4887	0.8483	0.9775	0.8652	0.9607
Machine	0.8461	0.6490	0.8173	0.8173	0.8173	0.8894
Glass	0.7009	0.6963	0.5935	0.4953	0.7009	0.7149
Voting	0.9149	0.9333	0.9517	0.9425	0.9563	0.9333
Wdbc	0.9490	0.6274	0.9367	0.9349	0.9332	0.9139
Balance scale	0.9024	0.952	0.7488	0.9088	0.7920	0.7712
Breast	0.9570	0.3462	0.9399	0.9613	0.9399	0.9341
Crx	0.8710	0.5565	0.8232	0.7522	0.8406	0.7754
Tic-tac-toe	0.6952	1.0000	0.7328	0.7150	0.8779	0.9624
Average	0.8808	0.7415	0.8385	0.8571	0.8716	0.8839