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Table 4 Average AUC and Partial AUC scores in Human.

From: A mixture of feature experts approach for protein-protein interaction prediction

Method

AUC mean

AUC std

R50 mean

R50 std

R100 mean

R100 std

LR

0.9419

0.020

0.1148

0.031

0.1684

0.031

NB

0.9389

0.003

0.0964

0.031

0.1356

0.035

RF

0.9427

0.009

0.0740

0.025

0.1263

0.030

SVM

0.7645

0.091

0.0455

0.028

0.0589

0.040

MFE

0.9608

0.007

0.1341

0.023

0.1759

0.027

MFE-FM

0.9384

0.018

0.1297

0.023

0.1713

0.025

  1. Average AUC and partial AUC scores for six classification methods for PPI prediction in human. LR: Logistic regression; NB: Naive Bayes; RF: Random Forest; SVM: Support Vector Machine; MFE: Mixture-of-Feature-Experts; MFE-FM: Mixture-of-Feature-Experts with missing values filled. Average AUC and partial AUC scores are reported and the standard derivations for each score estimation are also listed in the table. MFE scores are highlighted and it again achieves better AUC/R50/R100 scores compared to the other five classifiers.