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Table 1 Comparison of model performances built with five different machine learning algorithms. LightGBM performed better than the other four algorithms, with the highest AUC in all the four discrimination tasks (health vs IBD and UC vs CD) and the highest AP in three out of four tasks

From: LightCUD: a program for diagnosing IBD based on human gut microbiome data

Discrimination tasks WGS
Health vs IBD
WGS
UC vs CD
16S
Health vs IBD
16S
UC vs CD
Machine learning algorithm AUC AP AUC AP AUC AP AUC AP
Logistic regression 0.791 0.693 0.741 0.317 0.650 0.579 0.780 0.328
Random forest 0.941 0.887 0.935 0.486 0.909 0.855 0.931 0.498
Gradient boosting classifier 0.784 0.713 0.797 0.271 0.739 0.650 0.830 0.359
SVM 0.837 0.733 0.782 0.329 0.775 0.708 0.863 0.289
LightGBM 0.964 0.955 0.942 0.848 0.968 0.963 0.966 0.917
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