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  "Title": "Fast, Robust, and Outlier Resistant Hierarchical Clustering",
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  "Date": "2025-05-28",
  "Authors@R": "c(\nperson(\"Marek\", \"Gagolewski\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"marek@gagolewski.com\",\ncomment = c(ORCID = \"0000-0003-0637-6028\")),\nperson(\"Maciej\", \"Bartoszuk\", role = \"aut\",\nemail = \"bartoszuk@rexamine.com\",\ncomment = c(ORCID = \"0000-0001-6088-8273\")),\nperson(\"Anna\", \"Cena\", role = \"aut\",\nemail = \"cena@rexamine.com\",\ncomment = c(ORCID = \"0000-0001-8697-5383\"))\n)",
  "Description": "Includes the reference implementation of Genie - a\nhierarchical clustering algorithm that links two point groups\nin such a way that an inequity measure (namely, the Gini index)\nof the cluster sizes does not significantly increase above a\ngiven threshold. This method most often outperforms many other\ndata segmentation approaches in terms of clustering quality as\ntested on a wide range of benchmark datasets. At the same time,\nGenie retains the high speed of the single linkage approach,\ntherefore it is also suitable for analysing larger data sets.\nFor more details see (Gagolewski et al. 2016\n<DOI:10.1016/j.ins.2016.05.003>). For an even faster and more\nfeature-rich implementation, including, amongst others, noise\npoint detection, see the 'genieclust' package (Gagolewski, 2021\n<DOI:10.1016/j.softx.2021.100722>).",
  "License": "GPL (>= 3)",
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  "URL": "http://genieclust.gagolewski.com/\nhttps://github.com/gagolews/genie",
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