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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)