From: Multiclass classification of microarray data with repeated measurements: application to cancer
Data | Parameters | EWUSC | USC | SC | Published results |
---|---|---|---|---|---|
NCI 60 data* | ρ0 | NA | 0.6 | 1.0 | NA |
Δ | NA | 1.0 | 1.0 | NA | |
Number of relevant genes | NA | 2,315 | 3998 | 200 | |
Prediction accuracy | NA | 72% | 72% | ~40-60% [23] | |
Multiple tumor data (estimated optimal parameters)† | ρ0 | 0.8 | 0.8 | 1.0 | NA |
Δ | 5.6 | 5.6 | 8.8 | NA | |
Number of relevant genes | 680 | 735 | 3902 | All genes | |
Prediction accuracy | 93% | 85% | 78% | 78% [10] | |
Multiple tumor data (global optimal parameters)‡ | ρ0 | 0.9 | 0.9 | 1.0 | NA |
Δ | 0 | 0 | 0.4 | NA | |
Number of relevant genes | 1626 | 1634 | 7129 | All genes | |
Prediction accuracy | 78% | 74% | 74% | 78% [10] | |
Breast cancer data | ρ0 | 0.7 | 0.6 | 1.0 | NA |
Δ | 0.80 | 1.15 | 1.1 | NA | |
Number of relevant genes | 271 | 82 | 187 | 70 | |
Prediction accuracy | 89% | 79% | 84% | 89% [14] |