{
  "annotation_id": "2b3fbede-0d9a-4e10-9779-67e2075c8895",
  "date_created": "2026-03-02T18:00:32.286000Z",
  "date_modified": "2026-03-02T18:00:32.286000Z",
  "file_hash": "915ad639f5491448be1281248a432d653b35fa38c13ffc188860b8bd0758b3b0",
  "private": false,
  "record": {
    "abstract": "We introduce a method for validation of results obtained by clustering\nanalysis of data. The method is based on resampling the available data. A\nfigure of merit that measures the stability of clustering solutions against\nresampling is introduced. Clusters which are stable against resampling give\nrise to local maxima of this figure of merit. This is presented first for a\none-dimensional data set, for which an analytic approximation for the figure of\nmerit is derived and compared with numerical measurements. Next, the\napplicability of the method is demonstrated for higher dimensional data,\nincluding gene microarray expression data.",
    "arxiv_id": "physics/0005046",
    "authors": [
      "Erel Levine",
      "Eytan Domany"
    ],
    "categories": [
      "physics.comp-ph"
    ],
    "title": "Resampling Method For Unsupervised Estimation Of Cluster Validity",
    "url": "https://arxiv.org/abs/physics/0005046"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "a6134d23-b22b-4eab-86b0-5e4bf19cd4ae",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}