{
  "_id": "6a107406acfb0bcc41cac378",
  "Package": "FeaLect",
  "Type": "Package",
  "Title": "Scores Features for Feature Selection",
  "Version": "1.20",
  "Date": "2020-02-25",
  "Author": "Habil Zare",
  "Maintainer": "Habil Zare <zare@u.washington.edu>",
  "Description": "For each feature, a score is computed that can be useful\nfor feature selection. Several random subsets are sampled from\nthe input data and for each random subset, various linear\nmodels are fitted using lars method. A score is assigned to\neach feature based on the tendency of LASSO in including that\nfeature in the models.Finally, the average score and the models\nare returned as the output. The features with relatively low\nscores are recommended to be ignored because they can lead to\noverfitting of the model to the training data. Moreover, for\neach random subset, the best set of features in terms of global\nerror is returned. They are useful for applying Bolasso, the\nalternative feature selection method that recommends the\nintersection of features subsets.",
  "License": "GPL (>= 2)",
  "LazyLoad": "yes",
  "Packaged": {
    "Date": "2026-05-07 05:42:30 UTC",
    "User": "root"
  },
  "NeedsCompilation": "no",
  "RoxygenNote": "6.0.1",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2020-02-25 16:30:06 UTC",
  "RemoteUrl": "https://github.com/cran/FeaLect",
  "RemoteRef": "HEAD",
  "RemoteSha": "eb2479f6382d7e75c628cb04780215c2926017a7",
  "MD5sum": "fcab8ad4785d55c8c4073bc2cb4fc640",
  "_user": "cran",
  "_type": "src",
  "_file": "FeaLect_1.20.tar.gz",
  "_fileid": "7eceef27212d5f7094b1cc1da91fe1ed161f9a125abbac9c631f1657351a6fe5",
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  "_sha256": "7eceef27212d5f7094b1cc1da91fe1ed161f9a125abbac9c631f1657351a6fe5",
  "_created": "2026-05-07T05:42:30.000Z",
  "_published": "2026-05-22T15:19:34.713Z",
  "_distro": "noble",
  "_jobs": [
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      "config": "linux-devel-x86_64",
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  "_buildurl": "https://github.com/r-universe/cran/actions/runs/25478031911",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/cran/FeaLect",
  "_commit": {
    "id": "eb2479f6382d7e75c628cb04780215c2926017a7",
    "author": "Habil Zare <zare@u.washington.edu>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 1.20\n",
    "time": 1582648206
  },
  "_maintainer": {
    "name": "Habil Zare",
    "email": "zare@u.washington.edu"
  },
  "_registered": true,
  "_dependencies": [
    {
      "package": "lars",
      "role": "Depends"
    },
    {
      "package": "rms",
      "role": "Depends"
    }
  ],
  "_owner": "cran",
  "_selfowned": false,
  "_usedby": 0,
  "_updates": [],
  "_tags": [],
  "_stars": 2,
  "_userbio": {
    "uuid": 6899542,
    "type": "organization",
    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
  },
  "_downloads": {
    "count": 196,
    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/FeaLect"
  },
  "_mentions": 6,
  "_searchresults": 23,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/FeaLect.html",
    "manual.pdf"
  ],
  "_realowner": "cran",
  "_cranurl": false,
  "_releases": [
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      "version": "1.1",
      "date": "2010-11-03"
    },
    {
      "version": "1.3",
      "date": "2012-10-29"
    },
    {
      "version": "1.7",
      "date": "2014-12-31"
    },
    {
      "version": "1.8",
      "date": "2015-03-08"
    },
    {
      "version": "1.10",
      "date": "2015-05-12"
    },
    {
      "version": "1.12",
      "date": "2018-05-16"
    },
    {
      "version": "1.14",
      "date": "2018-06-01"
    },
    {
      "version": "1.20",
      "date": "2020-02-25"
    }
  ],
  "_exports": [
    "compute.balanced",
    "compute.logistic.score",
    "doctor.validate",
    "FeaLect",
    "ignore.redundant",
    "input.check.FeaLect",
    "random.subset",
    "train.doctor"
  ],
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      "title": "MCL and SLL lymphoma subtypes",
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      "file": "mcl_sll.rda",
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  ],
  "_help": [
    {
      "page": "FeaLect-package",
      "title": "Scores Features for Feature Selection",
      "topics": [
        "FeaLect-package"
      ]
    },
    {
      "page": "compute.balanced",
      "title": "Balances between negative and positive samples by oversampling.",
      "topics": [
        "compute.balanced"
      ]
    },
    {
      "page": "compute.logistic.score",
      "title": "Fits a logistic regression model using the linear scores",
      "topics": [
        "compute.logistic.score"
      ]
    },
    {
      "page": "doctor.validate",
      "title": "Validates a model using validating samples.",
      "topics": [
        "doctor.validate"
      ]
    },
    {
      "page": "FeaLect",
      "title": "Computes the scores of the features.",
      "topics": [
        "FeaLect"
      ]
    },
    {
      "page": "ignore.redundant",
      "title": "Refines a feature matrix",
      "topics": [
        "ignore.redundant"
      ]
    },
    {
      "page": "input.check.FeaLect",
      "title": "Checks the inputs to Fealect() function.",
      "topics": [
        "input.check.FeaLect"
      ]
    },
    {
      "page": "mcl_sll",
      "title": "MCL and SLL lymphoma subtypes",
      "topics": [
        "mcl_sll"
      ]
    },
    {
      "page": "random.subset",
      "title": "Selects a random subset of the input.",
      "topics": [
        "random.subset"
      ]
    },
    {
      "page": "train.doctor",
      "title": "Fits various models based on a combination on penalized linear models and logistic regression.",
      "topics": [
        "train.doctor"
      ]
    }
  ],
  "_rundeps": [
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    "base64enc",
    "bslib",
    "cachem",
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    "withr",
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  ],
  "_vignettes": [
    {
      "source": "FeaLect_feature_scorer.Rnw",
      "filename": "FeaLect_feature_scorer.pdf",
      "title": "Feature seLection by computing statistical scores",
      "engine": "utils::Sweave",
      "headings": [],
      "created": "2014-12-03",
      "modified": "2018-05-16 19:37:36",
      "commits": 3
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  "_score": 3.440909082065218,
  "_indexed": true,
  "_nocasepkg": "fealect",
  "_universes": [
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