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Table 5 Effects of training data size on prediction performance (AUC) for yeast

From: Protein-protein interaction prediction based on multiple kernels and partial network with linear programming

  G tt 15000 G tt 14000 G tt 13000
\(\phantom {\dot {i}\!}{RL}_{ {WOLP-K-1}:G_{tn}\sim 5394} \) 0.8658 - -
\( {RL}_{G_{tn}\sim 7394} \) 0.7931 - -
\(\phantom {\dot {i}\!} {RL}_{ {EW-K}:G_{tn}\sim 5394} \) 0.7519 - -
\(\phantom {\dot {i}\!} {RL}_{ {WOLP-K-1}:G_{tn}\sim 5394} \) - 0.8659 -
\( {RL}_{G_{tn}\sim 8394} \) - 0.8538 -
\(\phantom {\dot {i}\!} {RL}_{ {EW-K}:G_{tn}\sim 5394} \) - 0.7537 -
\(\phantom {\dot {i}\!} {RL}_{ {WOLP-K-1}:G_{tn}\sim 5394} \) - - 0.8659
\( {RL}_{G_{tn}\sim 9394} \) - - 0.8619
\(\phantom {\dot {i}\!} {RL}_{ {EW-K}:G_{tn}\sim 5394} \) - - 0.7520