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Table 4 Dataset D: classification performance of Ph-CNN compared to other classifiers on Healthy vs. CDf classification task

From: Phylogenetic convolutional neural networks in metagenomics

CDf Ph-CNN LSVM
p MCC min CI max CI MCC min CI max CI
65 0.785 0.775 0.795 0.781 0.776 0.785
130 0.832 0.825 0.840 0.833 0.829 0.838
195 0.896 0.891 0.901 0.910 0.907 0.912
259 0.927 0.924 0.930 0.920 0.918 0.923
  MLPNN RF
p MCC min CI max CI MCC min CI max CI
65 0.604 0.593 0.614 0.764 0.760 0.769
130 0.821 0.817 0.825 0.805 0.800 0.810
195 0.830 0.825 0.836 0.863 0.860 0.867
259 0.858 0.854 0.862 0.880 0.877 0.883
  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)