co-citation cluster analysis
1Cluster analysis — The result of a cluster analysis shown as the coloring of the squares into three clusters. Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more… …
2Analysis of variance — In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of… …
3Cluster effect — The cluster effect is the effect of buyers and sellers of a particular good or service congregating in a certain place and hence inducing other buyers and sellers to relocate there as well. Contents 1 The Silicon Valley case 2 Generalization 3… …
4Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… …
5Factor analysis — is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved, uncorrelated variables called factors. In other words, it is possible, for example, that variations in …
6Coma Cluster — This article is about the cluster of galaxies named the Coma Cluster. For the star cluster, see Coma star cluster. Coma Cluster A Sloan Digital Sky Survey/Spitzer Space Telescope image of the Coma Cluster in ultraviolet and visible light Courtesy …
7Race (classification of humans) — Race Classification Race (classification of humans) Genetics …
8Data mining — Not to be confused with analytics, information extraction, or data analysis. Data mining (the analysis step of the knowledge discovery in databases process,[1] or KDD), a relatively young and interdisciplinary field of computer science[2][3] is… …
9Mixture model — See also: Mixture distribution In statistics, a mixture model is a probabilistic model for representing the presence of sub populations within an overall population, without requiring that an observed data set should identify the sub population… …
10Determining the number of clusters in a data set — Determining the number of clusters in a data set, a quantity often labeled k as in the k means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. For a certain …
