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Theory and rationale of interpretable all-in-one pattern discovery and disentanglement system
In machine learning (ML), association patterns in the data, paths in decision trees, and weights between layers of the neural network are often entangled due to multiple underlying causes, thus masking the pattern-to-source relation, weakening prediction, and defying explanation. This paper presents...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203344/ https://www.ncbi.nlm.nih.gov/pubmed/37217691 http://dx.doi.org/10.1038/s41746-023-00816-9 |