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A Hyperparameter-Free, Fast and Efficient Framework to Detect Clusters From Limited Samples Based on Ultra High-Dimensional Features
Clustering is a challenging problem in machine learning in which one attempts to group N objects into K(0) groups based on P features measured on each object. In this article, we examine the case where N ≪ P and K(0) is not known. Clustering in such high dimensional, small sample size settings has n...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237044/ https://www.ncbi.nlm.nih.gov/pubmed/37275750 http://dx.doi.org/10.1109/access.2022.3218800 |