Cargando…
Global Considerations in Hierarchical Clustering Reveal Meaningful Patterns in Data
BACKGROUND: A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the on...
Autores principales: | Varshavsky, Roy, Horn, David, Linial, Michal |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2008
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375056/ https://www.ncbi.nlm.nih.gov/pubmed/18493326 http://dx.doi.org/10.1371/journal.pone.0002247 |
Ejemplares similares
-
UFFizi: a generic platform for ranking informative features
por: Gottlieb, Assaf, et al.
Publicado: (2010) -
Efficient algorithms for accurate hierarchical clustering of huge datasets: tackling the entire protein space
por: Loewenstein, Yaniv, et al.
Publicado: (2008) -
Entropy-driven partitioning of the hierarchical protein space
por: Rappoport, Nadav, et al.
Publicado: (2014) -
Considerations for supporting meaningful stakeholder engagement in global mental health research
por: Murphy, Jill K.
Publicado: (2022) -
A functional hierarchical organization of the protein sequence space
por: Kaplan, Noam, et al.
Publicado: (2004)