Interpretation of microbiota-based diagnostics by explaining individual classifier decisions
Abstract Background The human microbiota is associated with various disease states and holds a great promise for non-invasive diagnostics. However, microbiota data is challenging for traditional diagnostic approaches: It is high-dimensional, sparse and comprises of high inter-personal variation. Sta...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-10-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1843-1 |