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Table 13 Dataset D on IBD: classification performance of Ph-CNN compared to other classifiers on Healthy vs. iCDf classification task

From: Phylogenetic convolutional neural networks in metagenomics

iCDf

Ph-CNN

LSVM

p

MCC

min CI

max CI

MCC

min CI

max CI

62

0.704

0.655

0.753

0.534

0.484

0.583

124

0.702

0.642

0.760

0.414

0.346

0.482

186

0.680

0.614

0.738

0.662

0.605

0.718

247

0.681

0.614

0.739

0.561

0.507

0.621

 

MLPNN

RF

p

MCC

min CI

max CI

MCC

min CI

max CI

62

0.679

0.622

0.739

0.787

0.746

0.831

124

0.690

0.634

0.743

0.811

0.766

0.854

186

0.685

0.630

0.742

0.791

0.741

0.836

247

0.708

0.652

0.764

0.775

0.730

0.820

  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)