Browsing University of Waterloo by Subject "interpretable machine learning"
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MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenome-assembled genomes
(University of Waterloo, 2022-05-19)We propose MT-MAG, a novel machine learning-based software tool for the complete or partial hierarchically-structured taxonomic classification of metagenome-assembled genomes (MAGs). MT-MAG is capable of classifying large ... -
Studying CNN representations through activation dimensionality reduction and visualization
(University of Waterloo, 2021-10-01)The field of explainable artificial intelligence (XAI) aims to explain the decisions of DNNs. Complete DNN explanations accurately reflect the inner workings of the DNN while interpretable explanations are easy for humans ...