Dataset: 941 features selected on 10X GE, then 10X GE -> AML PBMC_D11T1 gene score (original prediction by Seurat: Acc: 0.647 ARI: 0.409 MacroF1: 0.486, by MLP: Acc: 0.543 ARI: 0.169 MacroF1: 0.410)
Tao has tried the pytorch implemented version but it seems having some problem in the author's implementation. I thus tried the original tensorflow version published by the author.
Experiments
Accuracy
ARI
MacroF1
Training Evaluation (no ADDA)
0.9997
0.9989
0.9998
Test Evaluation (no ADDA)
0.4473
0.0906
0.3454
Training Evaluation (ADDA, 2000 epoch)
0.9303
0.8352
0.9199
Test Evaluation (ADDA, 2000 epoch)
0.6232
0.3785
0.4336
Check discriminator performance by distinguishing between gene expression and gene score.