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...'clusters'' ← divide ''training'' into |''codebook''| clusters, where each cluster contains all vectors in ''training'' who are best represented by the corres '''for each''' cluster ''cluster'' in ''clusters'' '''do''' ...

...ges |first=Uzi |last=Vishkin |publisher=Class notes of courses on parallel algorithms taught since 1992 at the University of Maryland, College Park, Tel Aviv Uni ...en referred to as "[[sequential algorithm]]s", by contrast with concurrent algorithms. ...

...a [[Taxonomy (biology)|taxonomy]] using numeric algorithms like [[cluster analysis]] rather than using subjective evaluation of their properties. The concept ...

...uence is not matched then it becomes the representative sequence for a new cluster. The similarity score is often based on [[sequence alignment]]. Sequence cl ...s]]. Determining a representative [[tertiary structure]] for each sequence cluster is the aim of many [[structural genomics]] initiatives. ...

...[[swarm intelligence]] and naturally inspired search and [[optimisation]] algorithms which includes [[ant colony optimization]], [[particle swarm optimization]] ...ffusion mechanism, high-quality solutions can be identified from [[Cluster analysis|clusters]] of agents with the same hypothesis. The operation of SDS is most ...

...orm of clustering in which each [[data point]] can belong to more than one cluster. ...s]] involves assigning data points to clusters such that items in the same cluster are as similar as possible, while items belonging to different clusters are ...

classification, where the inputs tend to cluster in two groups. A large set of ...[k-nearest neighbor algorithm]], which is related to transductive learning algorithms.<ref>Advances in Information Retrieval: 37th European Conference on IR Rese ...

...hms can also be used to cluster data into predicted groupings in [[cluster analysis]]. In many compression algorithms, the ranking is equivalent to probability mass function estimation. Given t ...

...ommunity ecology]], the term "classification" normally refers to [[cluster analysis]]. ...t of output value to a given input value. Other examples are [[regression analysis|regression]], which assigns a real-valued output to each input; [[sequence ...

==Algorithms and theory== * ISAAC – [[International Symposium on Algorithms and Computation]] ...

...d in [[amortized analysis]] in computer science, especially in analysis of algorithms * Aggregate, in the social sciences, a gathering of people into a cluster or a crowd that does not form a true [[social group]] ...

== Clustering algorithms == ...ill, clustering techniques coming from artificial neural networks, genetic algorithms, or fuzzy logic are more efficient within large, multidimensional databases ...

| genre = [[List of numerical-analysis software|Technical computing]] * '''cluster''': [[hierarchical clustering]], [[vector quantization]], [[K-means cluster ...

...ain objects used by other algorithms, the medoid is an actual point in the cluster. ==Algorithms== ...

| thesis_title = Analysis and Implementation of Distributed Algorithms for Multi-Robot Systems ...onomous robots to mimic the behavior of bees, including their abilities to cluster, disperse, follow, and orbit.<ref>{{Cite web|title=James McLurkin {{!}} Lem ...

...the structure of complex systems or processes, in order to perform system analysis, project planning and organization design. Don Steward coined the term "des * The presentation is amenable to matrix-based analysis techniques, which can be used to improve the structure of the system. ...

...) and this kind of semantic labeling is the scope of the '''logical layout analysis'''. Document layout analysis is the union of geometric and logical labeling. It is typically performed b ...

...th>\mathcal{B}</math>, that is, the mean distance between elements of each cluster: ...en the joined clusters <math>\mathcal{A} \cup \mathcal{B}</math> and a new cluster <math>X</math> is given by the proportional averaging of the <math>d_{\mat ...

...g volume]]. There are several fast and simple bounding sphere construction algorithms with a high practical value in real-time computer graphics applications.{{r Such spheres are useful in [[Cluster analysis|clustering]], where groups of similar data points are classified together. ...

[[Category:Cluster analysis algorithms]] ...