BMC Bioinformatics

Table 3 The performance of the proposed pipeline when applied on CRC2 dataset, in terms of mean AUC, precision (P), recall (R) and F-measure (F), and their standard deviation

From: Taxonomy-aware feature engineering for microbiome classification

		BL				HFE
		AUC	P	R	F	AUC	P	R	F
DT	Score	0.697	0.700	0.700	0.700	0.657	0.692	0.617	0.582
DT	std.	0.160	0.210	0.270	0.200	0.158	0.226	0.150	0.174
NB	Score	0.647	0.650	0.650	0.650	0.583	0.566	0.550	0.515
NB	std.	0.200	0.290	0.290	0.250	0.217	0.214	0.150	0.163
RF	Score	0.669	0.674	0.667	0.663	0.975	0.915	0.883	0.884
RF	std.	0.200	0.240	0.290	0.220	0.075	0.104	0.130	0.130
Features		count: 6807				count: 28 std. 10.677

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ISSN: 1471-2105

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