Cluster analysis divides data into subsections that are meaningful and useful. This is an important tool in the social sciences, biology, statistics, pattern recognition and, now, marketing.

Course TopicsCluster analysis is a number of different algorithms and techniques for grouping objects sharing similar characteristics. Researchers in many areas face problems such as how to organize ...

Multivariate analysis techniques may be used for several purposes, such as dimension reduction, clustering, or classification. The primary goal of this short course is to help researchers who want to ...

Our Data Science Lab guru explains how to implement the k-means technique for data clustering, or cluster analysis, which is the process of grouping data items so that similar items belong to the same ...

This paper reports a Bayesian approach for the automatic identification of the optimal clustering proposal in the analysis of single-molecule localization-based super-resolution data.

Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 44, No. 1 (1995), pp. 101-112 (12 pages) This paper describes the use of cluster analysis to determine market segments in ...

The study, “Using Artificial Intelligence to Determine the Impact of E-Commerce on the Digital Economy,” builds a fused indicator matrix spanning ICT infrastructure, payments, trade and logistics, ...

We consider the analysis of clustered data using linear mixed effects models and generalized estimating equations, where covariates can be decomposed into between- and within-cluster components. Under ...

Avoiding the formation of unwanted clusters of similar elements when dividing data into groups is of great importance for the ...