Table 3.

Comparison of proposed method with Lasso, elastic net, adaptive Lasso, using three experimental mixtures containing 6, 7, and 20 metabolites, respectively; and a library size of 61, 101, and 200 metabolites, respectively. Performance was evaluated based on average accuracy, sensitivity, and specificity

|$\#$| Met.MetricsProposed methodLassoElastic NetAdaptive LassoChenomxBayesilASICS
Library size 61
 Accuracy1.000.720.620.750.800.640.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity1.000.690.580.730.820.600.81
 Accuracy1.000.770.790.640.890.640.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity1.000.740.760.590.910.590.86
20Accuracy0.930.670.690.700.740.750.56
 Sensitivity1.001.001.001.000.800.950.45
 Specificity0.900.510.540.560.710.660.59
Library size 101
 Accuracy0.940.790.880.720.870.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.940.780.870.710.880.250.81
 Accuracy0.970.900.840.870.930.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.890.830.860.950.370.86
 Accuracy0.880.720.730.720.690.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.850.650.670.650.670.160.59
Library size 200
 Accuracy0.940.860.860.830.920.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.930.850.850.820.930.250.81
 Accuracy0.980.860.860.920.960.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.850.850.920.970.370.86
 Accuracy0.860.740.750.740.760.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.840.710.720.710.750.160.59
|$\#$| Met.MetricsProposed methodLassoElastic NetAdaptive LassoChenomxBayesilASICS
Library size 61
 Accuracy1.000.720.620.750.800.640.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity1.000.690.580.730.820.600.81
 Accuracy1.000.770.790.640.890.640.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity1.000.740.760.590.910.590.86
20Accuracy0.930.670.690.700.740.750.56
 Sensitivity1.001.001.001.000.800.950.45
 Specificity0.900.510.540.560.710.660.59
Library size 101
 Accuracy0.940.790.880.720.870.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.940.780.870.710.880.250.81
 Accuracy0.970.900.840.870.930.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.890.830.860.950.370.86
 Accuracy0.880.720.730.720.690.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.850.650.670.650.670.160.59
Library size 200
 Accuracy0.940.860.860.830.920.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.930.850.850.820.930.250.81
 Accuracy0.980.860.860.920.960.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.850.850.920.970.370.86
 Accuracy0.860.740.750.740.760.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.840.710.720.710.750.160.59
Table 3.

Comparison of proposed method with Lasso, elastic net, adaptive Lasso, using three experimental mixtures containing 6, 7, and 20 metabolites, respectively; and a library size of 61, 101, and 200 metabolites, respectively. Performance was evaluated based on average accuracy, sensitivity, and specificity

|$\#$| Met.MetricsProposed methodLassoElastic NetAdaptive LassoChenomxBayesilASICS
Library size 61
 Accuracy1.000.720.620.750.800.640.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity1.000.690.580.730.820.600.81
 Accuracy1.000.770.790.640.890.640.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity1.000.740.760.590.910.590.86
20Accuracy0.930.670.690.700.740.750.56
 Sensitivity1.001.001.001.000.800.950.45
 Specificity0.900.510.540.560.710.660.59
Library size 101
 Accuracy0.940.790.880.720.870.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.940.780.870.710.880.250.81
 Accuracy0.970.900.840.870.930.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.890.830.860.950.370.86
 Accuracy0.880.720.730.720.690.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.850.650.670.650.670.160.59
Library size 200
 Accuracy0.940.860.860.830.920.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.930.850.850.820.930.250.81
 Accuracy0.980.860.860.920.960.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.850.850.920.970.370.86
 Accuracy0.860.740.750.740.760.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.840.710.720.710.750.160.59
|$\#$| Met.MetricsProposed methodLassoElastic NetAdaptive LassoChenomxBayesilASICS
Library size 61
 Accuracy1.000.720.620.750.800.640.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity1.000.690.580.730.820.600.81
 Accuracy1.000.770.790.640.890.640.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity1.000.740.760.590.910.590.86
20Accuracy0.930.670.690.700.740.750.56
 Sensitivity1.001.001.001.000.800.950.45
 Specificity0.900.510.540.560.710.660.59
Library size 101
 Accuracy0.940.790.880.720.870.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.940.780.870.710.880.250.81
 Accuracy0.970.900.840.870.930.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.890.830.860.950.370.86
 Accuracy0.880.720.730.720.690.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.850.650.670.650.670.160.59
Library size 200
 Accuracy0.940.860.860.830.920.300.80
6Sensitivity1.001.001.001.000.671.000.57
 Specificity0.930.850.850.820.930.250.81
 Accuracy0.980.860.860.920.960.420.83
7Sensitivity1.001.001.001.000.711.000.33
 Specificity0.970.850.850.920.970.370.86
 Accuracy0.860.740.750.740.760.330.56
20Sensitivity1.001.001.001.000.800.950.45
 Specificity0.840.710.720.710.750.160.59
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