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Table 10 Dataset D on IBD: classification performance of Ph-CNN compared to other classifiers on Healthy vs. UCr classification task

From: Phylogenetic convolutional neural networks in metagenomics

UCr

Ph-CNN

LSVM

p

MCC

min CI

max CI

MCC

min CI

max CI

60

0.445

0.375

0.517

0.509

0.221

0.384

119

0.464

0.393

0.537

0.533

0.238

0.357

178

0.444

0.372

0.520

0.519

0.328

0.449

237

0.346

0.283

0.536

0.408

0.303

0.420

 

MLPNN

RF

p

MCC

min CI

max CI

MCC

min CI

max CI

60

0.415

0.350

0.476

0.508

0.425

0.584

119

0.528

0.463

0.596

0.455

0.387

0.525

178

0.538

0.471

0.610

0.435

0.363

0.504

237

0.489

0.417

0.557

0.400

0.337

0.463

  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)