Table 5 Average metrics with standard deviations across 100 iterations for each drug repurposing data set
From: Joint embedding–classifier learning for interpretable collaborative filtering
AUC | NS-AUC | NDCG | ||
|---|---|---|---|---|
Gottlieb | Fast.ai | 0.90± 0.0 | 0.50± 0.1 | 0.01± 0.0 |
HAN | 0.93± 0.0 | 0.67± 0.0 | 0.02± 0.0 | |
NIM | 0.90± 0.0 | 0.51± 0.0 | 0.01± 0.0 | |
JELI | 0.90± 0.0 | 0.52± 0.0 | 0.02± 0.0 | |
LRSSL | Fast.ai | 0.90± 0.0 | 0.49± 0.1 | 0.01± 0.0 |
HAN | 0.95± 0.0 | 0.69± 0.0 | 0.10± 0.0 | |
NIM | 0.91± 0.0 | 0.53± 0.0 | 0.01± 0.0 | |
JELI | 0.92± 0.0 | 0.51± 0.0 | 0.02± 0.0 | |
PRED-G | Fast.ai | 0.90± 0.0 | 0.50± 0.1 | 0.01± 0.0 |
HAN | 0.93± 0.0 | 0.68± 0.0 | 0.01± 0.0 | |
NIM | 0.91± 0.0 | 0.49± 0.0 | 0.01± 0.0 | |
JELI | 0.90± 0.0 | 0.47± 0.0 | 0.02± 0.0 | |
TRANSC | Fast.ai | 0.61± 0.1 | 0.57± 0.1 | 0.04± 0.0 |
HAN | 0.93± 0.0 | 0.61± 0.0 | 0.08± 0.0 | |
NIM | 0.92± 0.0 | 0.57± 0.0 | 0.04± 0.0 | |
JELI | 0.92± 0.0 | 0.56± 0.0 | 0.02± 0.0 |