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Table 4 Proteomics ovarian cancer data

From: An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data

 

Accuracy

Sensitivity

Specificity

AUC

RF

0.9550

0.9639

0.9520

0.9924

SVM

0.9350

0.9021

0.9731

0.9795

PLS + RF

0.9050

0.9040

0.9029

0.9703

PLS + LDA

0.9600

0.9639

0.9624

0.9784

PLS + QDA

0.9550

0.9539

0.9648

0.9781

Ensemble

0.9650

0.9639

0.9711

0.9871

  1. Averages of 5-fold cross validation for the proteomics ovarian cancer data.
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BMC Bioinformatics

ISSN: 1471-2105

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