In statistics, single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerative...

clusters. Strategies for hierarchical clustering generally fall into two categories: Agglomerative: Agglomerative clustering, often referred to as a "bottom-up"...

Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. At the beginning of the process, each element is in a cluster of...

algorithm. Neighbor-joining Cluster analysis Single-linkage clustering Complete-linkage clustering Hierarchical clustering Models of DNA evolution Molecular...

average linkage clustering). Furthermore, hierarchical clustering can be agglomerative (starting with single elements and aggregating them into clusters) or...

assembled to reconstruct the original mRNA. Some clustering algorithms use single-linkage clustering, constructing a transitive closure of sequences with...

Ward's method, complete-linkage clustering, and single-linkage clustering; these all work by repeatedly merging the closest two clusters but use different definitions...

Complete linkage clustering avoids a drawback of the alternative single linkage clustering method - the so-called chaining phenomenon, where clusters formed...

basis for clustering, and ways to choose the number of clusters, to choose the best clustering model, to assess the uncertainty of the clustering, and to...

Dijkstra's algorithm Borůvka's algorithm Reverse-delete algorithm Single-linkage clustering Greedy geometric spanner Kleinberg, Jon (2006). Algorithm design...

spanning trees are closely related to single-linkage clustering, one of several methods for hierarchical clustering. The edges of a minimum spanning tree...

Taxonomy. Cluster analysis: clustering points in the plane, single-linkage clustering (a method of hierarchical clustering), graph-theoretic clustering, and...

Families in Cellular Manufacturing Systems Using an ART-Modified Single Linkage Clustering Approach – A Comparative Study" by M. Murugan and V. Selladurai...

Hierarchical clustering Single-linkage clustering Conceptual clustering Cluster analysis BIRCH DBSCAN Expectation–maximization (EM) Fuzzy clustering Hierarchical...

graphing linkage data sets is called Hierarchical Clustering. Clustering organizes things into groups based on similarity. In the case of linkage, similarity...

common schemes for performing the grouping, the two simplest being single-linkage clustering, in which two groups are considered separate communities if and...

clustering OPTICS: a density based clustering algorithm with a visual evaluation method Single-linkage clustering: a simple agglomerative clustering algorithm...

(econometrics) Simultaneous equations model Single equation methods (econometrics) Single-linkage clustering Singular distribution Singular spectrum analysis...

several other problems in this computational model, including single-linkage clustering and geometric minimum spanning trees. However, proving the 1-vs-2...

based on the same concepts. DeLi-Clu, Density-Link-Clustering combines ideas from single-linkage clustering and OPTICS, eliminating the ε {\displaystyle \varepsilon...

Document clustering (or text clustering) is the application of cluster analysis to textual documents. It has applications in automatic document organization...

iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large...

Automatic clustering algorithms are algorithms that can perform clustering without prior knowledge of data sets. In contrast with other clustering techniques...

Consensus clustering is a method of aggregating (potentially conflicting) results from multiple clustering algorithms. Also called cluster ensembles or...

below would be clustering. For example, nuclear profiles that contain similar genomic loci could be clustered together by k-means clustering or some variation...

corresponding cluster centroid. Thus the purpose of K-means clustering is to classify data based on similar expression. K-means clustering algorithm and...

Hierarchical clustering (including the fast SLINK, CLINK, NNChain and Anderberg algorithms) Single-linkage clustering Leader clustering DBSCAN (Density-Based...

genes shared among the input proteomes using single-linkage hierarchical clustering or markov clustering. The latest iteration of SonicParanoid uses machine...

results of a cluster analysis by permuting the rows and the columns of a matrix to place similar values near each other according to the clustering. This idea...

the clustering algorithm. Several standard clustering algorithms such as single linkage, complete linkage, and group average method have a recursive formula...