An overview of capabilities for cluster analysis of data found in the STATISTICA ADVANCED software package

Authors: Tikhonov I.A.
Published in issue: #1(18)/2018
DOI: 10.18698/2541-8009-2018-1-230
Category: Informatics, Computer Engineering and Control | Chapter: System Analysis, Control, and Information Processing, Statistics
Keywords: data analysis, cluster analysis, clustering, unsupervised classification, STATISTICA, Euclidean space, hierarchical and non-hierarchical clustering methods, joining/tree clustering, k-mean clustering, two-way joining
Published: 20.12.2017

The article reviews data clustering capabilities of the STATISTICA software package. We describe the clustering methods found in this product and the specifics of working with them from a practical standpoint. We consider the concept of distance measure between elements of the initial set and certain methods of clustering the initial set of observations, as well as cluster analysis results produced by the algorithms implemented in the STATISTICA Advanced package. There is no doubt that cluster analysis of data is highly relevant and pertinent at present, since data and data analysis results play an increasingly significant role in the information society of today, and clustering provides a better understanding of these data.

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