Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
URL: http://stat.ethz.ch/R-manual/R-patched/library/stats/html/hclust.html
Proper Citation: Hierarchical Clustering (RRID:SCR_014673)
Description: R documentation for hierarchical cluster analysis on a set of dissimilarities for n objects. Each object is assigned to its own cluster, which an algorithm proceeds through iteratively. Two of the most similar clusters are joined at each stage until there is a single cluster. Distances between clusters are recomputed at each stage by the Lance–Williams dissimilarity update formula according to the particular clustering method being used. Clustering methods include: Ward's minimum variance method, complete linkage method, and single linkage method.
Synonyms: R: Hierarchical Clustering, R - Hierarchical Clustering
Resource Type: software resource, software application, data analysis software, source code, data processing software
Keywords: statistical analysis, statistical analysis package, r, r package, data analysis, software, cluster, hierarchical, dissimilarity, clustering method, metabolomics
Expand Allis listed by |
We found {{ ctrl2.mentions.total_count }} mentions in open access literature.
We have not found any literature mentions for this resource.
We are searching literature mentions for this resource.
Most recent articles:
{{ mention._source.dc.creators[0].familyName }} {{ mention._source.dc.creators[0].initials }}, et al. ({{ mention._source.dc.publicationYear }}) {{ mention._source.dc.title }} {{ mention._source.dc.publishers[0].name }}, {{ mention._source.dc.publishers[0].volume }}({{ mention._source.dc.publishers[0].issue }}), {{ mention._source.dc.publishers[0].pagination }}. (PMID:{{ mention._id.replace('PMID:', '') }})
A list of researchers who have used the resource and an author search tool
A list of researchers who have used the resource and an author search tool. This is available for resources that have literature mentions.
No rating or validation information has been found for Hierarchical Clustering.
No alerts have been found for Hierarchical Clustering.
Source: SciCrunch Registry