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- W801704611 abstract "Cluster interpretation has an important role in the proper understanding of a set of classes, independently if they have been automatically discovered or they are expert-based. This understanding is crucial for further use of these classes as the basis of a decision-making process. Most of the works found in literature about post-processing the result of a clustering process correspond to the cluster validation using indexes. These cluster validity indexes evaluate the clusters from the structural point of view [1]. However, structural validation does not ensure the usefulness of the clustering, while meaningfulness is the key to guarantee that classes could support further decisions. Nevertheless, few references on Cluster Interpretation can be found. Some, rank the variables by their significance [3], others describe the centroids of the classes or are more concentrated in visualization [4]. However, the most common method for interpreting is a manual analysis of both expert and analysts. As the number of variables and/or classes increases, this process becomes tedious. Thus, cluster interpretation" @default.
- W801704611 created "2016-06-24" @default.
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- W801704611 date "2014-01-01" @default.
- W801704611 modified "2023-09-24" @default.
- W801704611 title "The role of statistical tests on cluster interpretation" @default.
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