In statistics, single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerative...
17 KB (2,496 words) - 01:05, 12 November 2024
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...
14 KB (2,170 words) - 02:21, 7 May 2025
Strategies for hierarchical clustering generally fall into two categories: Agglomerative: Agglomerative: Agglomerative clustering, often referred to as a...
31 KB (3,496 words) - 11:28, 23 May 2025
UPGMA (category Cluster analysis algorithms)
algorithm. Neighbor-joining Cluster analysis Single-linkage clustering Complete-linkage clustering Hierarchical clustering Models of DNA evolution Molecular...
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Nearest-neighbor chain algorithm (category Cluster analysis algorithms)
Ward's method, complete-linkage clustering, and single-linkage clustering; these all work by repeatedly merging the closest two clusters but use different definitions...
27 KB (3,651 words) - 00:34, 6 June 2025
assembled to reconstruct the original mRNA. Some clustering algorithms use single-linkage clustering, constructing a transitive closure of sequences with...
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average linkage clustering). Furthermore, hierarchical clustering can be agglomerative (starting with single elements and aggregating them into clusters) or...
75 KB (9,513 words) - 02:05, 30 April 2025
WPGMA (category Cluster analysis algorithms)
Complete linkage clustering avoids a drawback of the alternative single linkage clustering method - the so-called chaining phenomenon, where clusters formed...
11 KB (1,714 words) - 07:17, 9 July 2024
spanning trees are closely related to single-linkage clustering, one of several methods for hierarchical clustering. The edges of a minimum spanning tree...
55 KB (6,676 words) - 19:53, 5 February 2025
Dijkstra's algorithm Borůvka's algorithm Reverse-delete algorithm Single-linkage clustering Greedy geometric spanner Kleinberg, Jon (2006). Algorithm design...
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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...
32 KB (3,525 words) - 20:04, 9 June 2025
Taxonomy. Cluster analysis: clustering points in the plane, single-linkage clustering (a method of hierarchical clustering), graph-theoretic clustering, and...
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Families in Cellular Manufacturing Systems Using an ART-Modified Single Linkage Clustering Approach – A Comparative Study" by M. Murugan and V. Selladurai...
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OPTICS algorithm (category Cluster analysis algorithms)
based on the same concepts. DeLi-Clu, Density-Link-Clustering combines ideas from single-linkage clustering and OPTICS, eliminating the ε {\displaystyle \varepsilon...
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Hierarchical clustering Single-linkage clustering Conceptual clustering Cluster analysis BIRCH DBSCAN Expectation–maximization (EM) Fuzzy clustering Hierarchical...
39 KB (3,386 words) - 19:51, 2 June 2025
graphing linkage data sets is called Hierarchical Clustering. Clustering organizes things into groups based on similarity. In the case of linkage, similarity...
12 KB (1,460 words) - 00:35, 7 October 2023
Community structure (section Hierarchical clustering)
common schemes for performing the grouping, the two simplest being single-linkage clustering, in which two groups are considered separate communities if and...
37 KB (4,591 words) - 20:57, 1 November 2024
Automatic clustering algorithms are algorithms that can perform clustering without prior knowledge of data sets. In contrast with other cluster analysis...
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BIRCH (redirect from Birch clustering method for large databases)
iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large...
13 KB (2,275 words) - 14:43, 28 April 2025
several other problems in this computational model, including single-linkage clustering and geometric minimum spanning trees. However, proving the 1-vs-2...
4 KB (421 words) - 23:29, 12 January 2025
Microarray analysis techniques (section Clustering)
corresponding cluster centroid. Thus the purpose of K-means clustering is to classify data based on similar expression. K-means clustering algorithm and...
31 KB (3,567 words) - 04:54, 11 June 2025
clustering OPTICS: a density based clustering algorithm with a visual evaluation method Single-linkage clustering: a simple agglomerative clustering algorithm...
72 KB (7,951 words) - 17:13, 5 June 2025
below would be clustering. For example, nuclear profiles that contain similar genomic loci could be clustered together by k-means clustering or some variation...
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Document clustering (or text clustering) is the application of cluster analysis to textual documents. It has applications in automatic document organization...
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Hierarchical clustering (including the fast SLINK, CLINK, NNChain and Anderberg algorithms) Single-linkage clustering Leader clustering DBSCAN (Density-Based...
19 KB (2,106 words) - 07:06, 8 January 2025
Consensus clustering is a method of aggregating (potentially conflicting) results from multiple clustering algorithms. Also called cluster ensembles or...
22 KB (2,951 words) - 05:21, 11 March 2025
(econometrics) Simultaneous equations model Single equation methods (econometrics) Single-linkage clustering Singular distribution Singular spectrum analysis...
87 KB (8,280 words) - 23:04, 12 March 2025
Ward's method (category Cluster analysis algorithms)
the clustering algorithm. Several standard clustering algorithms such as single linkage, complete linkage, and group average method have a recursive formula...
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sets of alleles or DNA sequences can be clustered so that a single SNP can identify many linked SNPs. Linkage disequilibrium (LD), a term used in population...
58 KB (6,253 words) - 23:44, 28 April 2025
percolation properties to prove existence of O(n) expected time single linkage clustering algorithm at a predetermined threshold". ResearchGate. January...
9 KB (877 words) - 13:44, 13 May 2025