Table 1 Simulation summary
Parameters/methods | Values/descriptions |
|---|---|
Gene block standard deviation |
|
Gene block correlation |
|
Gene block size |
|
Noise level |
|
MV rate |
|
No. of marker genes | 30 |
No. of total genes | 500 |
Training sample size | 60 |
Testing sample size | 200 |
No. of repetitions for each model | 150 |
Imputation algorithms | RAVG, KNN, LLS.L2, LLS.PC, LS, BPCA |
Classification rules | LDA, 3NN, SVM |
Feature selection methods |
|
-test, SFFS