Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality
The application of machine learning to inference problems in biology is dominated by supervised learning problems of regression and classification, and unsupervised learning problems of clustering and variants of low-dimensional projections for visualization. A class of problems that have not gained...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
The Royal Society
2020-02-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.190714 |