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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)