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Table 7 The experimental results of dataset M2

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
0.01	0.653	0.657	0.641	0.631	0.616	0.620	0.637	0.640	0.638	0.648
0.02	0.653	0.657	0.641	0.631	0.616	0.620	0.637	0.640	0.638	0.648
0.03	0.653	0.657	0.641	0.631	0.616	0.620	0.637	0.640	0.637	0.645
Laplace method
0.01	0.626	0.623	0.629	0.625	0.636	0.617	0.610	0.628	0.586	0.460
0.02	0.626	0.623	0.629	0.625	0.636	0.617	0.610	0.628	0.586	0.459
0.03	0.626	0.623	0.629	0.625	0.636	0.617	0.610	0.628	0.586	0.450
Scoring method
0.01	0.671	0.671	0.671	0.671	0.671	0.671	0.671	0.671	0.672	0.671
0.02	0.671	0.671	0.671	0.671	0.671	0.671	0.671	0.671	0.672	0.671
0.03	0.671	0.671	0.671	0.671	0.671	0.671	0.671	0.671	0.672	0.672
Max χ² method
0.01	0.575	0.579	0.513	0.516	0.503	0.509	0.551	0.556	0.595	0.603
0.02	0.575	0.579	0.513	0.516	0.503	0.509	0.551	0.556	0.595	0.604
0.03	0.575	0.579	0.513	0.516	0.503	0.509	0.551	0.556	0.596	0.597

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