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  "Title": "Influential Points Detection for Feature Rankings",
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  "Date": "2024-11-20",
  "Authors@R": "c(\nperson(\"Shuo\", \"Wang\", , \"wangsures@foxmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0000-0424-2160\")),\nperson(\"Junyan\", \"Lu\", , \"junyan.lu@uni-heidelberg.de\", role = \"aut\")\n)",
  "Description": "Feature rankings can be distorted by a single case in the\ncontext of high-dimensional data. The cases exerts abnormal\ninfluence on feature rankings are called influential points\n(IPs). The package aims at detecting IPs based on case deletion\nand quantifies their effects by measuring the rank changes\n(DOI:10.48550/arXiv.2303.10516). The package applies a novel\nrank comparing measure using the adaptive weights that stress\nthe top-ranked important features and adjust the weights to\nranking properties.",
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  "URL": "https://github.com/ShuoStat/findIPs",
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  "Repository": "https://bioc-release.r-universe.dev",
  "Date/Publication": "2026-04-28 13:03:06 UTC",
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    "plotAdaptiveWeights",
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    "plotRankScatters",
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      "title": "miller05 data",
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    {
      "page": "findIPs",
      "title": "Function to detect influential points for feature rankings",
      "topics": [
        "findIPs"
      ]
    },
    {
      "page": "getdrop1ranks",
      "title": "Derive ranking lists including original and leave-one-out rankings",
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    },
    {
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      "title": "miller05 data",
      "topics": [
        "miller05"
      ]
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    {
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      "title": "Visualize the weight function for adaptive weights",
      "topics": [
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      ]
    },
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      "page": "plotIPs",
      "title": "Visualize the influential scores",
      "topics": [
        "plotIPs"
      ]
    },
    {
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      "title": "Visualize the unweighted rank changes",
      "topics": [
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      "title": "findIPs: Detect Influential Points for Feature Rankings",
      "author": "Shuo Wang, Junyan Lu",
      "engine": "knitr::rmarkdown",
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        "Installation",
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        "Results visualization",
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      "modified": "2024-03-19 14:41:44",
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