statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters...
26 KB (2,895 words) - 20:50, 25 July 2024
alternative clustering, multi-view clustering): objects may belong to more than one cluster; usually involving hard clusters Hierarchical clustering: objects...
69 KB (8,833 words) - 21:16, 5 August 2024
Hierarchical clustering is one method for finding community structures in a network. The technique arranges the network into a hierarchy of groups according...
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single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerative clustering), at...
17 KB (2,481 words) - 04:12, 22 June 2024
Dendrogram (category Cluster analysis)
frequently used in different contexts: in hierarchical clustering, it illustrates the arrangement of the clusters produced by the corresponding analyses...
6 KB (498 words) - 06:10, 12 January 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 its...
14 KB (2,170 words) - 00:40, 22 June 2024
DBSCAN (redirect from Density Based Spatial Clustering of Applications with Noise)
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg...
29 KB (3,489 words) - 17:09, 11 May 2024
K-medoids (redirect from K-medoids clustering)
Sadaaki; Kaizu, Yousuke; Endo, Yasunori (2016). Hierarchical and Non-Hierarchical Medoid Clustering Using Asymmetric Similarity Measures. 2016 Joint...
11 KB (1,418 words) - 08:13, 2 December 2023
graph. Tree structure Hierarchical query Hierarchical clustering Michael J. Kamfonas/Recursive Hierarchies: The Relational Taboo! Archived 2008-11-08...
6 KB (687 words) - 04:41, 16 February 2024
Hierarchical clustering Single-linkage clustering Conceptual clustering Cluster analysis BIRCH DBSCAN Expectation–maximization (EM) Fuzzy clustering Hierarchical...
41 KB (3,580 words) - 16:15, 14 June 2024
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 (2,276 words) - 16:07, 6 October 2023
p-values. Clustering is a data mining technique used to group genes having similar expression patterns. Hierarchical clustering, and k-means clustering are...
31 KB (3,559 words) - 08:05, 7 June 2024
{\displaystyle j} . The general approach to spectral clustering is to use a standard clustering method (there are many such methods, k-means is discussed...
23 KB (2,933 words) - 07:29, 11 December 2023
Ward's method (category Cluster analysis algorithms)
suggested a general agglomerative hierarchical clustering procedure, where the criterion for choosing the pair of clusters to merge at each step is based...
6 KB (1,107 words) - 19:26, 28 December 2023
Design Hierarchical Bayes model Hierarchical clustering Hierarchical clustering of networks Hierarchical constraint satisfaction Hierarchical linear modeling...
61 KB (5,982 words) - 13:26, 22 July 2024
Complete linkage (section Hierarchical Clustering)
for interpreting and graphing linkage data sets is called Hierarchical Clustering. Clustering organizes things into groups based on similarity. In the...
12 KB (1,460 words) - 00:35, 7 October 2023
Unrooted binary tree (section Hierarchical clustering)
structures, but in the applications of unrooted binary trees in hierarchical clustering and evolutionary tree reconstruction, unordered trees are more...
14 KB (1,961 words) - 05:14, 27 May 2024
Asteroid family (redirect from Hierarchical Clustering Method (asteroids))
asteroid families. The most prominent algorithms have been the hierarchical clustering method (HCM), which looks for groupings with small nearest-neighbour...
71 KB (2,445 words) - 11:00, 1 August 2024
Nearest-neighbor chain algorithm (category Cluster analysis algorithms)
of cluster analysis, the nearest-neighbor chain algorithm is an algorithm that can speed up several methods for agglomerative hierarchical clustering. These...
27 KB (3,649 words) - 00:35, 13 June 2024
UPGMA (category Cluster analysis algorithms)
method with arithmetic mean) is a simple agglomerative (bottom-up) hierarchical clustering method. It also has a weighted variant, WPGMA, and they are generally...
17 KB (2,430 words) - 07:09, 9 July 2024
Community structure (section Hierarchical clustering)
Another method for finding community structures in networks is hierarchical clustering. In this method one defines a similarity measure quantifying some...
38 KB (4,677 words) - 20:22, 12 May 2024
CURE algorithm (redirect from Cure data clustering)
(Clustering Using REpresentatives) is an efficient data clustering algorithm for large databases[citation needed]. Compared with K-means clustering it...
6 KB (778 words) - 22:09, 29 April 2022
Distance matrix (section Hierarchical clustering)
of hierarchical clustering is: Time complexity is O ( N 3 ) {\displaystyle O(N^{3})} due to the repetitive calculations done after every cluster to update...
31 KB (4,001 words) - 19:37, 5 June 2024
issue from the process of actually solving the clustering problem. For a certain class of clustering algorithms (in particular k-means, k-medoids and...
20 KB (2,750 words) - 07:12, 3 May 2024
WPGMA (category Cluster analysis algorithms)
Method with Arithmetic Mean) is a simple agglomerative (bottom-up) hierarchical clustering method, generally attributed to Sokal and Michener. The WPGMA method...
11 KB (1,714 words) - 07:17, 9 July 2024
Automatic clustering algorithms are algorithms that can perform clustering without prior knowledge of data sets. In contrast with other cluster analysis...
11 KB (1,385 words) - 06:42, 11 January 2024
nucleic acids The nearest neighbor clustering for calculating distances between clusters in hierarchical clustering Moore neighborhood Von Neumann neighborhood...
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Consensus clustering is a method of aggregating (potentially conflicting) results from multiple clustering algorithms. Also called cluster ensembles or...
22 KB (2,950 words) - 07:30, 16 July 2024
such as Bisecting k-means, X-means clustering and G-means clustering repeatedly split clusters to build a hierarchy, and can also try to automatically...
61 KB (7,688 words) - 21:51, 19 July 2024
contexts. In natural language processing, Brown clustering or IBM clustering is a form of hierarchical clustering of words based on the contexts in which they...
10 KB (1,198 words) - 01:48, 23 January 2024