DCMD: Distance-based classification using mixture distributions on microbiome data
Fig 3
Two-class outcome: boxplot of the accuracy over 100 replicates for each method and scenario.
The proposed DCMD method is shown in orange for k-means and k-NN with D-L2 and CC-L2 distances. The other distance-based methods are shown in blue, including k-means and k-NN with Euclidean and Manhattan distances and NSC. Machine learning methods are shown in green, including random forest (RF), gradient boosting (GB), LASSO, ridge regression (RR), support vector machine (SVM). The dashed red line gives the average accuracy of the best method in each scenario.