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Table 5 The experimental results of dataset BC

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	0.644	0.659	0.689	0.693	0.708	0.699	0.707	0.698	0.705	0.704
0.03	0.644	0.659	0.689	0.693	0.707	0.699	0.707	0.698	0.705	0.700
0.04	0.644	0.659	0.689	0.693	0.707	0.699	0.707	0.698	0.704	0.694
Laplace method
0.02	0.504	0.522	0.573	0.594	0.595	0.569	0.584	0.580	0.543	0.510
0.03	0.504	0.522	0.573	0.594	0.595	0.569	0.584	0.577	0.536	0.513
0.04	0.504	0.522	0.573	0.594	0.595	0.569	0.580	0.575	0.520	0.507
Scoring method
0.02	0.703	0.703	0.703	0.703	0.703	0.704	0.704	0.703	0.704	0.704
0.03	0.703	0.703	0.703	0.703	0.704	0.704	0.704	0.704	0.703	0.704
0.04	0.703	0.703	0.703	0.703	0.703	0.704	0.704	0.704	0.706	0.706
Max χ² method
0.02	0.514	0.513	0.558	0.550	0.547	0.590	0.600	0.618	0.624	0.620
0.03	0.514	0.513	0.558	0.550	0.547	0.590	0.600	0.618	0.624	0.613
0.04	0.514	0.513	0.558	0.550	0.547	0.590	0.600	0.618	0.621	0.587

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