Skip to main content

Table 3 Breast cancer microarray data

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

 

Accuracy

Sensitivity

Specificity

AUC

Count

SVM

0.5846

0.6679

0.5525

0.6845

168

PLR

0.6154

0.6859

0.5706

0.6503

197

PLS + RF

0.6077

0.6615

0.5562

0.6498

170

PLS + LDA

0.6846

0.6744

0.6887

0.6826

305

PLS + QDA

0.6462

0.7063

0.5799

0.6871

78

PCA + QDA

0.4692

0.3127

0.6645

0.5401

92

Ensemble

0.6385

0.6563

0.6227

0.7108

 
  1. Average of 10-fold cross validation for the breast cancer microarray data. The number of bootstraps N = 101. The count column shows the number of times a particular individual algorithm was a locally "best" performing classifier across all 10 folds.
Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us