# Cluster analysis

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Related to Cluster analysis: factor analysis, Discriminant 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.
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This is the most commonly used procedure in cluster analysis.
I'm well aware that the Cluster Analysis function is under the Statistics Add-on package, and as it said in my review, I had to find it under that section, which, as you correctly point out, is under the Add-on tab (this brings up two errors: one, I should have said 'Add-ons/ Statistics/Cluster Analysis' rather than 'Cluster Analysis/Statistics;' and two, I should have specified 'FindClusters' rather than 'Find Cluster' as the reference).
In the first stage, a cluster analysis program was employed by using residential addresses.
The result of cluster analysis is a number of heterogeneous groups with homogeneous contents.
Next, cluster analysis produced a series of 12 kernel maps based on date of symptom onset.
We propose a new methodology based on cluster analysis and analysis of variance (ANOVA) to solve this problem.
REMI representatives will demonstrate and give a hands-on workshop of its economic impact modeling system and other products on cluster analysis and transportation project analysis.
Cluster analysis uses a series of mathematical computations to identify groups that occur in data sets.
Among the topics are the effect of releasing information on searching for missing children: the case of the Baby Back Home network, forecasting treatment outcomes for the Futures drug and alcohol rehabilitation center, a novel approach to forecasting regression and cluster analysis, developing a practical and effective forecasting performance measure, and forecasting in-service supply chain systems: a state-of-the-art review using latent semantic analysis.
Text analytic software also can analyze structured data in ways that are not possible with IDEA, ACL, or visual analytic software, such as cluster analysis, market segmentation, and nearest neighbor capabilities.
PCoA divided genotypes into 4 groups in a similar pattern as generated with cluster analysis and authenticated the results of cluster analysis.
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