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DeepCoDA: personalized interpretability for compositional health data [article]

Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020 arXiv   pre-print
We propose the Deep Compositional Data Analysis (DeepCoDA) framework to extend precision health modelling to high-dimensional compositional data, and to provide personalized interpretability through patient-specific  ...  Our architecture maintains state-of-the-art performance across 25 real-world data sets, all while producing interpretations that are both personalized and fully coherent for compositional data.  ...  Supplemental Material for: DeepCoDA: personalized interpretability for compositional health data A.  ... 
arXiv:2006.01392v2 fatcat:eaqrvcpa4zd3zbg3mut5lcmb34