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1. Clustering (demographics): In demographics, clustering is the gathering of various populations based on ethnicity, economics, or religion. In countries that hold equality important, clustering occurs between groups because of polarizing factors such as religion, wealth or ethnocentrism. (Social) [100%] 2024-02-25 [Sociological terminology]
2. Cluttering: Cluttering is a speech and communication disorder characterized by a rapid rate of speech, erratic rhythm, and poor syntax or grammar, making speech difficult to understand. Cluttering is a speech and communication disorder that has also been described as a ... (Speech and communication disorder) [89%] 2023-06-13 [Communication disorders] [Sociolinguistics]...
3. Cluttering: Template:DiseaseDisorder infobox Articles Most recent articles on Cluttering Most cited articles on Cluttering Review articles on Cluttering Articles on Cluttering in N Eng J Med, Lancet, BMJ Media Powerpoint slides on Cluttering Images of Cluttering Photos of Cluttering Podcasts ... [89%] 2023-03-28 [Communication disorders] [Neurology]...
4. Clusterin: Clusterin (apolipoprotein J) is a 75 - 80 kDa disulfide-linked heterodimeric protein associated with the clearance of cellular debris and apoptosis. In humans, clusterin is encoded by the CLU gene on chromosome 8. [88%] 2023-10-18 [Proteins]
5. Behavioral clustering: Behavioral clustering is a statistical analysis method used in retailing to identify consumer purchase trends and group stores based on consumer buying behaviors. Historically, retailers and manufacturers have grouped stores based on top-down constraints such as store size, total ... (Finance) [70%] 2023-09-09 [Cluster analysis] [Retail analytics]...
6. Keyword clustering: Keyword clustering is a practice search engine optimization (SEO) professionals use to segment target search terms into groups (clusters) relevant to each page of the website. After keyword research, search engine professionals cluster keywords into small groups which they spread ... (Practice search engine optimization) [70%] 2023-12-28 [Search engine optimization]
7. Hierarchical clustering: Department of Computing and Mathematics, University of Derby, and Department of Computing, Goldsmiths University of London. Hierarchical clustering algorithms can be characterized as greedy (Horowitz and Sahni, 1979). (Mathematics) [70%] 2023-10-29 [Statprob]
8. Quantum clustering: Quantum Clustering (QC) is a class of data-clustering algorithms that use conceptual and mathematical tools from quantum mechanics. QC belongs to the family of density-based clustering algorithms, where clusters are defined by regions of higher density of data ... [70%] 2022-10-25 [Cluster analysis algorithms]
9. Brown clustering: Brown clustering is a hard hierarchical agglomerative clustering problem based on distributional information proposed by Peter Brown, William A. Brown, Vincent Della Pietra, Peter V. [70%] 2023-03-02 [Cluster analysis] [Language modeling]...
10. Key clustering: Key or hash function should avoid clustering, the mapping of two or more keys to consecutive slots. Such clustering may cause the lookup cost to skyrocket, even if the load factor is low and collisions are infrequent. (Social) [70%] 2023-05-27 [Key management]
11. Clustering coefficient: In graph theory, a clustering coefficient is a measure of the degree to which nodes in a graph tend to cluster together. Evidence suggests that in most real-world networks, and in particular social networks, nodes tend to create tightly ... (Measure of how connected and clustered a node is in its graph) [70%] 2023-11-20 [Graph invariants] [Algebraic graph theory]...
12. Hierarchical clustering: Hierarchical clustering (also known as numerical taxonomy) is a branch of cluster analysis which treats clusters hierarchically, i.e., as a set of levels. The construction of the hierarchy can be performed using two major approaches, or combinations thereof: In ... [70%] 2023-07-04
13. Volatility clustering: In finance, volatility clustering refers to the observation, first noted by Mandelbrot (1963), that "large changes tend to be followed by large changes, of either sign, and small changes tend to be followed by small changes." A quantitative manifestation of ... (Finance) [70%] 2024-01-06 [Derivatives (finance)] [Technical analysis]...
14. Consensus clustering: Consensus clustering is a method of aggregating (potentially conflicting) results from multiple clustering algorithms. Also called cluster ensembles or aggregation of clustering (or partitions), it refers to the situation in which a number of different (input) clusterings have been obtained ... [70%] 2023-03-04 [Cluster analysis]
15. Clustering illusion: Clustering illusion is the cognitive bias of seeing a pattern in what is actually a random sequence of numbers or events. It is a type of apophenia related to the gambler's fallacy. [70%] 2023-03-01 [Psychology]
16. Primary clustering: In computer programming, primary clustering is a phenomenon that causes performance degradation in linear-probing hash tables. The phenomenon states that, as elements are added to a linear probing hash table, they have a tendency to cluster together into long ... [70%] 2024-02-16 [Hashing]
17. Correlation clustering: Clustering is the problem of partitioning data points into groups based on their similarity. Correlation clustering provides a method for clustering a set of objects into the optimum number of clusters without specifying that number in advance. [70%] 2023-05-21 [Cluster analysis] [Computational problems in graph theory]...
18. Conceptual clustering: Conceptual clustering is a machine learning paradigm for unsupervised classification that has been defined by Ryszard S. Michalski in 1980 (Fisher 1987, Michalski 1980) and developed mainly during the 1980s. (Machine learning paradigm) [70%] 2024-02-15 [Learning methods] [Classification algorithms]...
19. Spectral clustering: In multivariate statistics, spectral clustering techniques make use of the spectrum (eigenvalues) of the similarity matrix of the data to perform dimensionality reduction before clustering in fewer dimensions. The similarity matrix is provided as an input and consists of a ... (Clustering methods) [70%] 2023-12-26 [Cluster analysis algorithms] [Algebraic graph theory]...
20. Clustering illusion: The clustering illusion is the tendency to erroneously consider the inevitable "streaks" or "clusters" arising in small samples from random distributions to be non-random. The illusion is caused by a human tendency to underpredict the amount of variability likely ... (Erroneously seeing patterns in randomness) [70%] 2023-11-15 [Cognitive biases] [Statistical randomness]...