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Table 6 The experimental results of dataset BCW

From: Building an associative classifier with multiple minimum supports

minsup	\(\sigma\)
minsup	1	0.9	0.8	0.7	0.6	0.5	0.4	0.3	0.2	0.1
Maximum likelihood method
0.02	0.926	0.926	0.923	0.925	0.933	0.945	0.946	0.952	0.953	0.953
0.03	0.948	0.947	0.943	0.942	0.948	0.959	0.959	0.962	0.963	0.963
0.04	0.943	0.942	0.938	0.937	0.944	0.954	0.955	0.959	0.959	0.959
Laplace method
0.02	0.808	0.823	0.852	0.885	0.916	0.914	0.930	0.944	0.950	0.945
0.03	0.705	0.728	0.795	0.859	0.902	0.906	0.917	0.927	0.923	0.894
0.04	0.776	0.811	0.862	0.895	0.926	0.920	0.922	0.923	0.916	0.912
Scoring method
0.02	0.752	0.748	0.754	0.763	0.769	0.759	0.766	0.763	0.770	0.767
0.03	0.715	0.713	0.711	0.709	0.708	0.704	0.709	0.709	0.712	0.715
0.04	0.714	0.712	0.715	0.718	0.719	0.720	0.723	0.724	0.726	0.721
Max χ² method
0.02	0.700	0.688	0.704	0.715	0.737	0.787	0.790	0.795	0.793	0.802
0.03	0.716	0.700	0.715	0.728	0.751	0.804	0.809	0.806	0.814	0.818
0.04	0.787	0.791	0.801	0.805	0.813	0.811	0.804	0.809	0.813	0.818

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