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Table 4 Dataset D: classification performance of Ph-CNN compared to other classifiers on Healthy vs. CDf classification task

From: Phylogenetic convolutional neural networks in metagenomics

CDf

Ph-CNN

LSVM

p

MCC

min CI

max CI

MCC

min CI

max CI

65

0.785

0.775

0.795

0.781

0.776

0.785

130

0.832

0.825

0.840

0.833

0.829

0.838

195

0.896

0.891

0.901

0.910

0.907

0.912

259

0.927

0.924

0.930

0.920

0.918

0.923

 

MLPNN

RF

p

MCC

min CI

max CI

MCC

min CI

max CI

65

0.604

0.593

0.614

0.764

0.760

0.769

130

0.821

0.817

0.825

0.805

0.800

0.810

195

0.830

0.825

0.836

0.863

0.860

0.867

259

0.858

0.854

0.862

0.880

0.877

0.883

  1. The performance measure is MCC, with 95% studentized bootstrap confidence intervals (min CI, max CI). Models are computed for p={25%,50%,75% and 100%} of total number of features for each task. Comparing algorithms are linear Support Vector Machines (LSVM), Random Forest (RF) and MultiLayer Perceptron (MLPNN)