Author: Jakub M Bartoszewicz; Anja Seidel; Bernhard Y Renard
Title: Interpretable detection of novel human viruses from genome sequencing data Document date: 2020_1_30
ID: ac00tai9_35
Snippet: . CC-BY-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10. 1101 /2020 To test this hypothesis, we use partial Shapley values. Intuitively speaking, we capture the contributions of a nucleotide to the network's output, but only in the context of a given intermediate neuron of the convolutional layer. More precisely, for any given.....
Document: . CC-BY-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10. 1101 /2020 To test this hypothesis, we use partial Shapley values. Intuitively speaking, we capture the contributions of a nucleotide to the network's output, but only in the context of a given intermediate neuron of the convolutional layer. More precisely, for any given feature x i , intermediate neuron y j and the output neuron z, we aim to measure how x i contributes to z while regarding only the fraction of the total contribution of x i that influences how y j contributes to z.
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