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Using the Kriging Correlation for unsupervised feature selection problems
This paper proposes a KC Score to measure feature importance in clustering analysis of high-dimensional data. The KC Score evaluates the contribution of features based on the correlation between the original features and the reconstructed features in the low dimensional latent space. A KC Score-base...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9263137/ https://www.ncbi.nlm.nih.gov/pubmed/35798813 http://dx.doi.org/10.1038/s41598-022-15529-4 |