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The recent advent of Metagenome-Wide Association Studies (MGWAS) has allowed for increased accuracy in the prediction of patient phenotype (disease), but has also presented big data challenges. Meanwhile, Multiple Instance Learning (MIL) is useful in the domain of bioinformatics because, in addition to classifying patient phenotype, it can also identify individual parts of the microbiome that are...
Classification problems in which several learning tasks are organized hierarchically pose a special challenge because the hierarchical structure of the problems needs to be considered. Multi-task learning (MTL) provides a framework for dealing with such interrelated learning tasks. When two different hierarchical sources organize similar information, in principle, this combined knowledge can be exploited...
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