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Object Cluster Hierarchies is a new variant of Hierarchical Cluster Analysisthat gains interest in the field of Machine Learning. Being still at an earlystage of development, the lack of tools for systematic analysis of ObjectCluster Hierarchies inhibits its further improvement. In this paper we addressthis issue by proposing a generator of synthetic hierarchical data that can beused for benchmarking Object Cluster Hierarchy methods. The article presents athorough empirical and theoretical analysis of the generator and providesguidance on how to control its parameters. Conducted experiments show theusefulness of the data generator that is capable of producing a wide range ofdifferently structured data. Further, benchmarking datasets that mirror themost common types of hierarchies are generated and made available to thepublic, together with the developed generator(http://kio.pwr.edu.pl/?page\_id=396).

Hierarchical Data Generator based on Tree-Structured Stick Breaking Process for Benchmarking Clustering Methods