Cluster analysis

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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.
References in periodicals archive ?
A simulated annealing (SA) based approach has been developed in [39], A tabu search (TS) based method was introduced in [2, 42], A genetic algorithm (GA) based methods was presented in [6, 16, 27, 31, 32], A comparison has been performed to investigate the computational performance of K-Means, SA, TS and GA for data clustering [3], Fathian et al.
A Data Clustering Algorithm Based On Single Hidden Markov Model".
PolyServe shared data clustering offers a unique approach to SQL Server consolidation.
PolyServe's unique shared data clustering software virtualizes industry-standard servers and storage as a single system to set new price-performance standards for file serving and server consolidation.
PolyServe Matrix Server(TM) shared data clustering software now supports Oracle(R) Database 10g on Linux.
PolyServe Matrix Server shared data clustering software now supports Oracle Database 10g on Linux.
0 uses 3D data visualization, pathway views and data clustering.
It extends the VERITAS core volume management, file system, and cluster server solutions to support shared data clustering.
Banding patterns were compared (8), and dendrograms of relatedness were constructed by data clustering using the unweighted pair grouping arithmetic averaging method (Molecular Fingerprinting Program version 1.
Prosper Intelligence delivers software based virtualization and high availability solutions, shared data clustering and backup solutions.
Currently, huge data clustering has been broadly analyzed over in several fields, including statistics, machine learning, pattern recognition, and image processing.