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Table 2 The results over imbalanced, trimmed and balanced data.

From: Prediction of protein-protein interaction sites using an ensemble method

Features

Dataset

AUC

Sensitivity

Specificity

Group 1

Imbalanced

0.71815

0.23618

0.95589

 

Trimmed

0.69259

0.60103

0.67216

 

Balanced

0.72944

0.62285

0.70575

Group 2

Imbalanced

0.74139

0.26960

0.96100

 

Trimmed

0.74575

0.73217

0.62533

 

Balanced

0.77802

0.69670

0.71086

Group 3

Imbalanced

0.81745

0.37526

0.95015

 

Trimmed

0.81670

0.72653

0.74426

 

Balanced

0.84647

0.76836

0.76798

Group 4

Imbalanced

0.80099

0.27180

0.96929

 

Trimmed

0.79362

0.72478

0.71542

 

Balanced

0.83079

0.73978

0.75002

  1. The imbalanced data includes all examples in the original datasets; the trimmed data owns all positive examples and randomly selected negative examples, with a 1:1 ratio of positive to negative examples; the balanced datasets are generated by Sub-EnClassifiers with resampling technique.