Generating Multidimensional Clusters With Support Lines

arXiv:2301.10327v3 Announce Type: replace
Abstract: Synthetic data is essential for assessing clustering techniques, complementing and extending real data, and allowing for more complete coverage of a given problem's space. In turn, synthetic data generators have the potential of creating vast amounts of data -- a crucial activity when real-world data is at premium -- while providing a well-understood generation procedure and an interpretable instrument for methodically investigating cluster analysis algorithms. Here, we present Clugen, a modular procedure for synthetic data …

abstract arxiv clustering coverage cs.cv cs.lg cs.pl data generators multidimensional real data space support synthetic synthetic data type vast world