A Bayesian Classifier Learning Algorithm Based on Optimization Model

Table 2

The detailed experimental results on accuracy and standard deviation.

NO.	Dataset	NB	TAN	BAN	BC-OM
1	Shuttle	83.52±5.85	𝟖𝟓.𝟑𝟑±𝟕.𝟎𝟑	84.43±6.83	82.33±5.94
2	Balloon	𝟖𝟗.𝟏𝟓±𝟑.𝟎𝟔	85.16±3.15	87.16±2.92	83.75±3.57
3	Lenses	92.56±2.44	93.25±2.85	89.67±3.16	91.12±3.02
4	Soybean (small)	90.91±2.35	84.98±3.16	87.36±2.44	89.74±3.23
5	Post-patient	80.29±3.39	79.94±3.47	𝟖𝟏.𝟐𝟔±𝟑.𝟓𝟔	80.12±3.48
6	Zoo	93.46±5.12	95.21±4.78	94.34±5.16	94.88±5.09
7	Hayes-roth	81.82±5.27	𝟖𝟕.𝟑𝟒±𝟒.𝟖𝟗	84.58±3.74	84.55±3.56
8	Iris	𝟗𝟒.𝟏𝟑±𝟔.𝟏𝟐	93.47±6.65	93.81±6.80	89.07±7.25
9	Glass	𝟔𝟔.𝟎𝟐±𝟗.𝟖𝟖	59.67±9.52	58.32±9.98	56.96±9.81
10	Heart	82.41±6.62	82.53±7.01	𝟖𝟐.𝟔𝟓±𝟕.𝟎𝟑	81.53±6.91
11	Ionosphere	90.54±4.03	90.61±3.98	𝟗𝟏.𝟒𝟓±𝟒.𝟏𝟒	𝟗𝟎.𝟗𝟗±𝟒.𝟖𝟐
12	Monk's	84.28±1.14	83.29±1.29	83.79±1.23	𝟖𝟔.𝟔𝟒±𝟏.𝟎𝟐
13	Vote	𝟗𝟒.𝟖𝟖±𝟑.𝟓𝟕	90.37±3.34	𝟗𝟐.𝟔𝟑±𝟑.𝟗𝟖	90.97±2.95
14	Balance-scale	𝟗𝟎.𝟗𝟏±𝟏.𝟓𝟏	84.97±2.44	87.94±2.31	𝟗𝟎.𝟕𝟕±𝟏.𝟖𝟓
15	Tic-tac-toe	70.11±4.45	73.16±4.47	75.74±4.83	𝟕𝟔.𝟐𝟏±𝟑.𝟖𝟐
16	Car-evaluation	84.95±2.74	93.44±1.89	89.2±1.02	𝟗𝟓.𝟒𝟐±𝟏.𝟎𝟑
17	Chess (kr-vs-kp)	87.88±1.91	91.68±1.66	90.27±1.12	𝟗𝟐.𝟔𝟓±𝟏.𝟒
18	Mushroom	92.85±0.56	99.89±0.1	96.37±0.76	𝟗𝟗.𝟗𝟏±𝟎.𝟏
19	Nursery	90.54±1.14	94.07±1.29	92.31±1.23	89.95±1.09
20	Letter	69.32±3.97	77.58±1.83	73.45±1.67	𝟕𝟕.𝟔𝟔±𝟐.𝟎𝟏
	Average	𝟖𝟔.𝟖𝟓±𝟒.𝟖𝟏	86.63±3.7	85.69±3.69	𝟖𝟔.𝟕𝟔±𝟑.𝟓𝟕