Table 5 Comparison of classification accuracy results from EWUSC, USC and SC on synthetic datasets at optimal parameters
From: Multiclass classification of microarray data with repeated measurements: application to cancer
α | Number of measurements | λ | EWUSC | USC | SC | ||
|---|---|---|---|---|---|---|---|
(a) Different noise levels with four repeated measurements | 0.1 | 4 | Low | 100% | 100% | 100% | Average % CV prediction accuracy |
100% | 100% | 100% | % prediction accuracy | ||||
10 | 24 | 72 | Number of genes | ||||
(18, 0.8) | (17, 0.7) | (17.5, 1) | (Δ, ρ) | ||||
0.1 | 4 | High | 100% | 100% | 100% | Average % CV prediction accuracy | |
100% | 100% | 100% | % prediction accuracy | ||||
8 | 16 | 22 | Number of genes | ||||
(12.5, 0.9) | (12.5, 0.9) | (12.5, 1) | (Δ, ρ) | ||||
1 | 4 | Low | 100% | 100% | 100% | Average % CV prediction accuracy | |
100% | 100% | 100% | % prediction accuracy | ||||
144 | 119 | 124 | Number of genes | ||||
(2.8, 0.5) | (3.1, 0.6) | (3.1, 1) | (Δ, ρ) | ||||
1 | 4 | High | 100% | 100% | 100% | Average % CV prediction accuracy | |
100% | 100% | 100% | % prediction accuracy | ||||
89 | 120 | 122 | Number of genes | ||||
(1.9, 0.5) | (2.6, 0.6) | (2.6, 1) | (Δ, ρ) | ||||
2 | 4 | Low | 96.8% | 99.0% | 98.8% | Average % CV prediction accuracy | |
97.5% | 100.0% | 100.0% | % prediction accuracy | ||||
270 | 326 | 326 | Number of genes | ||||
(1.1, 0.5) | (1, 0.4) | (1.2, 1) | (Δ, ρ) | ||||
2 | 4 | High | 93.3% | 98.8% | 99.0% | Average % CV prediction accuracy | |
92.5% | 97.5% | 97.5% | % prediction accuracy | ||||
186 | 159 | 159 | Number of genes | ||||
(1, 0.7) | (1.5, 0.5) | (1.5, 1) | (Δ, ρ) | ||||
(b) Different numbers of repeated measurements at high biological noise levels | 2 | 1 | Low | NA | 99.5% | 99.5% | Average % CV prediction accuracy |
NA | 100.0% | 100.0% | % prediction accuracy | ||||
NA | 285 | 304 | Number of genes | ||||
NA | (1.2, 0.5) | (1.2, 1) | (Δ, ρ) | ||||
2 | 1 | High | NA | 96.5% | 95.5% | Average % CV prediction accuracy | |
NA | 92.5% | 92.5% | % prediction accuracy | ||||
NA | 258 | 282 | Number of genes | ||||
NA | (1.2, 0.5) | (1.2, 1) | (Δ, ρ) | ||||
2 | 8 | Low | 99.8% | 100.0% | 100.0% | Average % CV prediction accuracy | |
100.0% | 100.0% | 100.0% | % prediction accuracy | ||||
246 | 220 | 221 | Number of genes | ||||
(1.3, 0.5) | (1.4, 0.5) | (1.4, 1) | (Δ, ρ) | ||||
2 | 8 | High | 98.3% | 99.0% | 99.0% | Average % CV prediction accuracy | |
97.5% | 100.0% | 100.0% | % prediction accuracy | ||||
171 | 242 | 245 | Number of genes | ||||
(1, 0.4) | (1.3, 0.5) | (1.3, 1) | (Δ, ρ) | ||||
2 | 20 | Low | 99.8% | 100.0% | 100.0% | Average % CV prediction accuracy | |
100.0% | 100.0% | 100.0% | % prediction accuracy | ||||
226 | 296 | 325 | Number of genes | ||||
(1.3, 0.5) | (1.2, 0.6) | (1.2, 1) | (Δ, ρ) | ||||
2 | 20 | High | 99.8% | 100.0% | 100.0% | Average % CV prediction accuracy | |
100.0% | 100.0% | 100.0% | % prediction accuracy | ||||
221 | 252 | 252 | Number of genes | ||||
(0.9, 0.6) | (1.3, 0.5) | (1.3, 1) | (Δ, ρ) |