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Table 9 The APM for different classifier methods

From: Application of pattern recognition tools for classifying acute coronary syndrome: an integrated medical modeling

Classifier Actual class Predicted class
STEMI NSTEMI UA Others
ANFIS STEMI 88.72 ± 4.82 8.14 ± 4.15 1.57 ± 1.80 1.57 ± 1.85
NSTEMI 31.21 ± 9.05 40.04 ± 9.19 23.33 ± 7.33 5.42 ± 4.53
UA 2.72 ± 1.91 17.43 ± 6.01 78.02 ± 5.93 1.84 ± 1.91
Others 5.79 ± 9.30 22.69 ±16.86 67.22 ±17.83 4.30 ± 6.71
7-nn STEMI 94.24 ± 3.22 4.20 ± 2.84 1.56 ± 1.52 0.00 ± 0.00
NSTEMI 31.07 ± 7.64 47.14 ± 8.72 21.78 ± 7.41 0.02 ± 0.22
UA 2.05 ± 1.32 3.64 ± 1.84 94.20 ± 2.23 0.11 ± 0.33
Others 7.44 ± 7.79 7.28 ± 7.77 85.23 ± 10.31 0.05 ± 0.80
Native Bayes STEMI 83.22 ± 4.78 2.59 ± 1.96 11.99 ± 3.94 2.19 ± 2.59
NSTEMI 20.06 ± 6.32 47.59 ± 7.40 28.98 ± 7.35 3.36 ± 2.96
UA 0.04 ± 0.20 7.16 ± 6.58 86.17 ± 7.23 6.64 ± 4.15
Others 0.84 ± 2.88 7.85 ±10.09 80.99 ±12.58 10.32 ± 8.85
ID3 STEMI 84.55 ± 5.81 13.3 ± 5.61 1.92 ± 1.88 0.23 ± 0.73
NSTEMI 26.59 ± 7.58 46.05 ± 9.00 25.09 ± 7.91 2.28 ± 2.99
UA 0.94 ± 0.94 6.05 ± 2.84 88.08 ± 3.76 4.93 ± 2.64
Others 3.09 ± 5.56 12.41 ± 10.70 78.63 ±13.60 5.87 ± 8.03
Bagging-ID3 STEMI 91.77 ± 3.94 6.54 ± 3.51 1.65 ± 1.73 0.03 ± 0.23
NSTEMI 30.59 ± 7.41 46.93 ± 7.29 22.32 ± 6.85 0.16 ± 0.72
UA 1.13 ± 0.85 3.70 ± 1.83 94.07 ± 2.36 1.09 ± 1.05
Others 3.21 ± 4.87 9.84 ± 8.05 85.00 ± 9.50 1.95 ± 4.30
RBF (7 neurons) STEMI 84.99± 4.98 1.76 ± 1.81 13.18 ± 4.74 0.07 ± 0.37
NSTEMI 30.67±17.98 34.88 ±17.88 33.98 ±10.00 0.47 ± 1.31
UA 2.34 ± 2.34 2.18 ± 1.73 95.41 ± 2.35 0.07 ± 0.27
Others 5.40± 8.81 8.37 ± 9.10 84.88 ±12.10 1.34 ± 3.81
MLP (9 neurons) STEMI 93.78 ± 5.05 2.67 ± 2.72 3.38 ± 4.07 0.17 ± 0.68
NSTEMI 29.93 ±10.41 48.33 ±10.21 21.43 ± 9.20 0.31 ± 1.14
UA 0.73 ± 1.26 2.98 ± 2.11 96.21 ± 2.55 0.08 ± 0.34
Others 3.07 ± 6.56 9.76 ± 12.30 82.54 ±15.10 4.62 ± 9.64