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Table 2 Effects of downsampling on the performance

From: Task-driven knowledge graph filtering improves prioritizing drugs for repurposing

Dataset

Model

Original (MRR)

Modified (MRR)

%-Change

Hetionet

TransE

0.2232

0.2374

\(+6.4\)

DistMult

0.2280

0.2517

\(+9.3\)

ComplEx

0.1975

0.2782

\(+40.8\)

RESCAL

0.2428

0.2940

\(+21.1\)

ConvE

0.1312

0.1647

\(+25.5\)

Random

0.0343

0.0331

\(-3.5\)

DRKG

TransE

0.0822

0.0938

\(+14.2\)

DistMult

0.0899

0.0931

\(+3.6\)

ComplEx

0.0896

0.0950

\(+5.9\)

RESCAL

0.0578*

0.0650*

\(+12.4\)

ConvE

0.0618*

0.0649*

\(+4.9\)

Random

0.0102

0.0086

\(-16.7\)

  1. *) Due to computational constraints, no hyperparameter optimization (HPO) has been performed for these models. The hyperparameter setting was chosen based on the results of the HPO on Hetionet