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Table 5 Dataset D: classification performance of Ph-CNN compared to other classifiers on Healthy vs. CDr classification task

From: Phylogenetic convolutional neural networks in metagenomics

CDr

Ph-CNN

LSVM

p

MCC

min CI

max CI

MCC

min CI

max CI

65

0.714

0.705

0.723

0.740

0.734

0.746

129

0.799

0.793

0.806

0.802

0.798

0.808

193

0.850

0.844

0.856

0.860

0.857

0.864

257

0.890

0.884

0.895

0.880

0.877

0.882

 

MLPNN

RF

p

MCC

min CI

max CI

MCC

min CI

max CI

65

0.498

0.473

0.521

0.688

0.682

0.695

129

0.783

0.778

0.788

0.744

0.740

0.784

193

0.766

0.759

0.773

0.762

0.756

0.767

257

0.788

0.782

0.794

0.765

0.761

0.771

  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)