Cargando…
Pattern discovery and disentanglement on relational datasets
Machine Learning has made impressive advances in many applications akin to human cognition for discernment. However, success has been limited in the areas of relational datasets, particularly for data with low volume, imbalanced groups, and mislabeled cases, with outputs that typically lack transpar...
Autores principales: | Wong, Andrew K. C., Zhou, Pei-Yuan, Butt, Zahid A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7952710/ https://www.ncbi.nlm.nih.gov/pubmed/33707478 http://dx.doi.org/10.1038/s41598-021-84869-4 |
Ejemplares similares
-
Theory and rationale of interpretable all-in-one pattern discovery and disentanglement system
por: Wong, Andrew K. C., et al.
Publicado: (2023) -
Explanation and prediction of clinical data with imbalanced class distribution based on pattern discovery and disentanglement
por: Zhou, Pei-Yuan, et al.
Publicado: (2021) -
Discovery and disentanglement of aligned residue associations from aligned pattern clusters to reveal subgroup characteristics
por: Zhou, Pei-Yuan, et al.
Publicado: (2018) -
Revealing Subtle Functional Subgroups in Class A Scavenger Receptors by Pattern Discovery and Disentanglement of Aligned Pattern Clusters
por: Zhou, Pei-Yuan, et al.
Publicado: (2018) -
In Search of Disentanglement in Tandem Mass Spectrometry Datasets
por: Abram, Krzysztof Jan, et al.
Publicado: (2023)