Constrained clustering; advances in algorithms, theory, and applications.9781584889960 Constrained clustering In computer science, constrained clustering is a class of semi-supervised learning algorithms. Typically, constrained clustering incorporates either a set of must-link constraints, cannot-link constraints, or both, with a Data clustering algorithm. ; advances in algorithms, theory, and applications. Ed. by Sugato Basu et al. Chapman & Hall/CRC 2009 441 pages $79.95 Hardcover Chapman & Hall/CRC data mining and knowledge discovery series QA278 Clustering algorithms take data with any number of dimensions and group them into subsets so each member of a subset A group of commands or functions that do not include all the capabilities of the original specification. Software or hardware components designed for the subset will also work with the original. is near the other members in some sense. In 17 articles including an introduction, contributors describe this phenomenon, focusing on semi-supervise clustering with user feedback, Gaussian mixture models with equivalence constraints, pairwise constraints as priors in probabilistic (probability) probabilistic - Relating to, or governed by, probability. The behaviour of a probabilistic system cannot be predicted exactly but the probability of certain behaviours is known. Such systems may be simulated using pseudorandom numbers. clustering, clustering with constraints using a mean-field approximation approximation /ap·prox·i·ma·tion/ (ah-prok?si-ma´shun) 1. the act or process of bringing into proximity or apposition. 2. a numerical value of limited accuracy. perspectives, constraint-driven co-clustering of 0/1 data, supervised clustering for creating categorization segmentations, clustering with balancing constraints, assignment constraints that avoid empty clusters in k-means clustering, collective relational clustering, non-redundant data clustering, joint cluster analysis Cluster analysis A statistical technique that identifies clusters of stocks whose returns are highly correlated within each cluster and relatively uncorrelated across clusters. Cluster analysis has identified groupings such as growth, cyclical, stable, and energy stocks. of attribute data and relationship data, correlation clustering, interactive visualization Interactive visualization is a branch of graphic visualization in computer science that studies how humans interact with computers to create graphic illustrations of information and how this process can be made more efficient. for relational data, distance metric learning, data publishing that preserves privacy, and learning with pairwise constraints for video object classification. ([c]20082005 Book News, Inc., Portland, OR) |
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