{
  "_id": "6a1ef4d1b401979e73416497",
  "Package": "mldr.datasets",
  "Title": "R Ultimate Multilabel Dataset Repository",
  "Version": "0.4.2",
  "Date": "2019-01-16",
  "Authors@R": "c(\nperson(\"David\", \"Charte\", email = \"fdavidcl@ugr.es\", role = \"cre\", comment = c(ORCID = \"0000-0002-4830-9512\")),\nperson(\"Francisco\", \"Charte\", email = \"francisco@fcharte.com\", role = \"aut\", comment = c(ORCID = \"0000-0002-3083-8942\")),\nperson(\"Antonio J.\", \"Rivera\", email = \"arivera@ujaen.es\", role = \"aut\"))",
  "Description": "Large collection of multilabel datasets along with the\nfunctions needed to export them to several formats, to make\npartitions, and to obtain bibliographic information.",
  "URL": "https://github.com/fcharte/mldr.datasets",
  "License": "LGPL (>= 3) | file LICENSE",
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  "Repository": "https://fcharte.r-universe.dev",
  "Date/Publication": "2019-03-12 17:32:28 UTC",
  "RemoteUrl": "https://github.com/fcharte/mldr.datasets",
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  "NeedsCompilation": "no",
  "Packaged": {
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  "Author": "David Charte [cre] (ORCID: <https://orcid.org/0000-0002-4830-9512>),\nFrancisco Charte [aut] (ORCID: <https://orcid.org/0000-0002-3083-8942>),\nAntonio J. Rivera [aut]",
  "Maintainer": "David Charte <fdavidcl@ugr.es>",
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  "_user": "fcharte",
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  "_created": "2026-05-19T07:03:13.000Z",
  "_published": "2026-06-02T15:20:49.537Z",
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  "_devurl": "https://github.com/fcharte/mldr.datasets",
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  "_assets": [
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    "extra/citation.json",
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  "_exports": [
    "available.mldrs",
    "bibtex",
    "bookmarks",
    "check_n_load.mldr",
    "corel16k001",
    "corel16k002",
    "corel16k003",
    "corel16k004",
    "corel16k005",
    "corel16k006",
    "corel16k007",
    "corel16k008",
    "corel16k009",
    "corel16k010",
    "corel5k",
    "delicious",
    "density",
    "enron",
    "eurlexdc_test",
    "eurlexdc_tra",
    "eurlexev_test",
    "eurlexev_tra",
    "eurlexsm_test",
    "eurlexsm_tra",
    "get.mldr",
    "imdb",
    "iterative.stratification.holdout",
    "iterative.stratification.kfolds",
    "iterative.stratification.partitions",
    "mediamill",
    "mldrs",
    "nuswide_BoW",
    "nuswide_VLAD",
    "ohsumed",
    "random.holdout",
    "random.kfolds",
    "random.partitions",
    "rcv1sub1",
    "rcv1sub2",
    "rcv1sub3",
    "rcv1sub4",
    "rcv1sub5",
    "reutersk500",
    "sparsity",
    "stackex_chemistry",
    "stackex_coffee",
    "stackex_cooking",
    "stackex_cs",
    "stackex_philosophy",
    "stratified.holdout",
    "stratified.kfolds",
    "stratified.partitions",
    "tmc2007",
    "tmc2007_500",
    "write.mldr",
    "yahoo_arts",
    "yahoo_business",
    "yahoo_computers",
    "yahoo_education",
    "yahoo_entertainment",
    "yahoo_health",
    "yahoo_recreation",
    "yahoo_reference",
    "yahoo_science",
    "yahoo_social",
    "yahoo_society",
    "yeast"
  ],
  "_datasets": [
    {
      "name": "birds",
      "title": "Dataset with sounds produced by birds and the species they belong to",
      "object": "birds",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "cal500",
      "title": "Dataset with music data along with labels for emotions, instruments, genres, etc.",
      "object": "cal500",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "emotions",
      "title": "Dataset with features extracted from music tracks and the emotions they produce",
      "object": "emotions",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "flags",
      "title": "Dataset with features correspoinding to world flags",
      "object": "flags",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "genbase",
      "title": "Dataset with genes data and their functional expression",
      "object": "genbase",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "langlog",
      "title": "Dataset with data from the Language forum discussion",
      "object": "langlog",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "medical",
      "title": "Dataset generated from medical reports",
      "object": "medical",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "ng20",
      "title": "Dataset with news messages and the news groups they belong to",
      "object": "ng20",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "slashdot",
      "title": "Dataset generated from slashdot.org site entries",
      "object": "slashdot",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "stackex_chess",
      "title": "Dataset from the Stack Exchange's chess forum",
      "object": "stackex_chess",
      "class": [
        "mldr"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
  ],
  "_help": [
    {
      "page": "available.mldrs",
      "title": "Obtain additional datasets available to download",
      "topics": [
        "available.mldrs"
      ]
    },
    {
      "page": "bibtex",
      "title": "Dataset with BibTeX entries",
      "topics": [
        "bibtex"
      ]
    },
    {
      "page": "birds",
      "title": "Dataset with sounds produced by birds and the species they belong to",
      "topics": [
        "birds"
      ]
    },
    {
      "page": "bookmarks",
      "title": "Dataset with data from web bookmarks and their categories",
      "topics": [
        "bookmarks"
      ]
    },
    {
      "page": "cal500",
      "title": "Dataset with music data along with labels for emotions, instruments, genres, etc.",
      "topics": [
        "cal500"
      ]
    },
    {
      "page": "check_n_load.mldr",
      "title": "(Defunct) Check if an mldr object is locally available and download it if needed",
      "topics": [
        "check_n_load.mldr"
      ]
    },
    {
      "page": "corel16k001",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k001"
      ]
    },
    {
      "page": "corel16k002",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k002"
      ]
    },
    {
      "page": "corel16k003",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k003"
      ]
    },
    {
      "page": "corel16k004",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k004"
      ]
    },
    {
      "page": "corel16k005",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k005"
      ]
    },
    {
      "page": "corel16k006",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k006"
      ]
    },
    {
      "page": "corel16k007",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k007"
      ]
    },
    {
      "page": "corel16k008",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k008"
      ]
    },
    {
      "page": "corel16k009",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k009"
      ]
    },
    {
      "page": "corel16k010",
      "title": "Datasets with data from the Corel image collection. There are 10 subsets in corel16k",
      "topics": [
        "corel16k010"
      ]
    },
    {
      "page": "corel5k",
      "title": "Dataset with data from the Corel image collection",
      "topics": [
        "corel5k"
      ]
    },
    {
      "page": "delicious",
      "title": "Dataset generated from the del.icio.us site bookmarks",
      "topics": [
        "delicious"
      ]
    },
    {
      "page": "density",
      "title": "Calculate the density level of the dataset",
      "topics": [
        "density"
      ]
    },
    {
      "page": "emotions",
      "title": "Dataset with features extracted from music tracks and the emotions they produce",
      "topics": [
        "emotions"
      ]
    },
    {
      "page": "enron",
      "title": "Dataset with email messages and the folders where the users stored them",
      "topics": [
        "enron"
      ]
    },
    {
      "page": "eurlexdc_test",
      "title": "List with 10 folds of the test data from the EUR-Lex directory codes dataset",
      "topics": [
        "eurlexdc_test"
      ]
    },
    {
      "page": "eurlexdc_tra",
      "title": "List with 10 folds of the train data from the EUR-Lex directory codes dataset",
      "topics": [
        "eurlexdc_tra"
      ]
    },
    {
      "page": "eurlexev_test",
      "title": "List with 10 folds of the test data from the EUR-Lex EUROVOC descriptors dataset",
      "topics": [
        "eurlexev_test"
      ]
    },
    {
      "page": "eurlexev_tra",
      "title": "List with 10 folds of the train data from the EUR-Lex EUROVOC descriptors dataset",
      "topics": [
        "eurlexev_tra"
      ]
    },
    {
      "page": "eurlexsm_test",
      "title": "List with 10 folds of the test data from the EUR-Lex subject matters dataset",
      "topics": [
        "eurlexsm_test"
      ]
    },
    {
      "page": "eurlexsm_tra",
      "title": "List with 10 folds of the train data from the EUR-Lex subject matters dataset",
      "topics": [
        "eurlexsm_tra"
      ]
    },
    {
      "page": "flags",
      "title": "Dataset with features correspoinding to world flags",
      "topics": [
        "flags"
      ]
    },
    {
      "page": "genbase",
      "title": "Dataset with genes data and their functional expression",
      "topics": [
        "genbase"
      ]
    },
    {
      "page": "get.mldr",
      "title": "Get a multilabel dataset by name",
      "topics": [
        "get.mldr"
      ]
    },
    {
      "page": "imdb",
      "title": "Dataset generated from the IMDB film database",
      "topics": [
        "imdb"
      ]
    },
    {
      "page": "iterative.stratification.holdout",
      "title": "Hold-out partitioning of an mldr object",
      "topics": [
        "iterative.stratification.holdout"
      ]
    },
    {
      "page": "iterative.stratification.kfolds",
      "title": "Partition an mldr object into k folds",
      "topics": [
        "iterative.stratification.kfolds"
      ]
    },
    {
      "page": "iterative.stratification.partitions",
      "title": "Generic partitioning of an mldr object",
      "topics": [
        "iterative.stratification.partitions"
      ]
    },
    {
      "page": "langlog",
      "title": "Dataset with data from the Language forum discussion",
      "topics": [
        "langlog"
      ]
    },
    {
      "page": "mediamill",
      "title": "Dataset with features extracted from video sequences and semantic concepts assigned as labels",
      "topics": [
        "mediamill"
      ]
    },
    {
      "page": "medical",
      "title": "Dataset generated from medical reports",
      "topics": [
        "medical"
      ]
    },
    {
      "page": "mldrs",
      "title": "(Defunct) Obtain and show a list of additional datasets available to download",
      "topics": [
        "mldrs"
      ]
    },
    {
      "page": "ng20",
      "title": "Dataset with news messages and the news groups they belong to",
      "topics": [
        "ng20"
      ]
    },
    {
      "page": "nuswide_BoW",
      "title": "Dataset obtained from the NUS-WIDE database with BoW representation",
      "topics": [
        "nuswide_BoW"
      ]
    },
    {
      "page": "nuswide_VLAD",
      "title": "Dataset obtained from the NUS-WIDE database with cVLAD+ representation",
      "topics": [
        "nuswide_VLAD"
      ]
    },
    {
      "page": "ohsumed",
      "title": "Dataset generated from a subset of the Medline database",
      "topics": [
        "ohsumed"
      ]
    },
    {
      "page": "random.holdout",
      "title": "Hold-out partitioning of an mldr object",
      "topics": [
        "random.holdout"
      ]
    },
    {
      "page": "random.kfolds",
      "title": "Partition an mldr object into k folds",
      "topics": [
        "random.kfolds"
      ]
    },
    {
      "page": "random.partitions",
      "title": "Generic partitioning of an mldr object",
      "topics": [
        "random.partitions"
      ]
    },
    {
      "page": "rcv1sub1",
      "title": "Dataset from the Reuters corpus (subset 1)",
      "topics": [
        "rcv1sub1"
      ]
    },
    {
      "page": "rcv1sub2",
      "title": "Dataset from the Reuters corpus (subset 2)",
      "topics": [
        "rcv1sub2"
      ]
    },
    {
      "page": "rcv1sub3",
      "title": "Dataset from the Reuters corpus (subset 3)",
      "topics": [
        "rcv1sub3"
      ]
    },
    {
      "page": "rcv1sub4",
      "title": "Dataset from the Reuters corpus (subset 4)",
      "topics": [
        "rcv1sub4"
      ]
    },
    {
      "page": "rcv1sub5",
      "title": "Dataset from the Reuters corpus (subset 5)",
      "topics": [
        "rcv1sub5"
      ]
    },
    {
      "page": "reutersk500",
      "title": "Dataset from the Reuters Corpus with the 500 most relevant features selected",
      "topics": [
        "reutersk500"
      ]
    },
    {
      "page": "scene",
      "title": "Dataset from images with different natural scenes",
      "topics": [
        "scene"
      ]
    },
    {
      "page": "slashdot",
      "title": "Dataset generated from slashdot.org site entries",
      "topics": [
        "slashdot"
      ]
    },
    {
      "page": "sparsity",
      "title": "Calculate the sparsity level of the dataset",
      "topics": [
        "sparsity"
      ]
    },
    {
      "page": "stackex_chemistry",
      "title": "Dataset from the Stack Exchange's chemistry forum",
      "topics": [
        "stackex_chemistry"
      ]
    },
    {
      "page": "stackex_chess",
      "title": "Dataset from the Stack Exchange's chess forum",
      "topics": [
        "stackex_chess"
      ]
    },
    {
      "page": "stackex_coffee",
      "title": "Dataset from the Stack Exchange's coffee forum",
      "topics": [
        "stackex_coffee"
      ]
    },
    {
      "page": "stackex_cooking",
      "title": "Dataset from the Stack Exchange's cooking forum",
      "topics": [
        "stackex_cooking"
      ]
    },
    {
      "page": "stackex_cs",
      "title": "Dataset from the Stack Exchange's computer science forum",
      "topics": [
        "stackex_cs"
      ]
    },
    {
      "page": "stackex_philosophy",
      "title": "Dataset from the Stack Exchange's philosophy forum",
      "topics": [
        "stackex_philosophy"
      ]
    },
    {
      "page": "stratified.holdout",
      "title": "Hold-out partitioning of an mldr object",
      "topics": [
        "stratified.holdout"
      ]
    },
    {
      "page": "stratified.kfolds",
      "title": "Partition an mldr object into k folds",
      "topics": [
        "stratified.kfolds"
      ]
    },
    {
      "page": "stratified.partitions",
      "title": "Generic partitioning of an mldr object",
      "topics": [
        "stratified.partitions"
      ]
    },
    {
      "page": "tmc2007",
      "title": "Dataset from airplanes failures reports",
      "topics": [
        "tmc2007"
      ]
    },
    {
      "page": "tmc2007_500",
      "title": "Dataset from airplanes failures reports (500 most relevant features extracted)",
      "topics": [
        "tmc2007_500"
      ]
    },
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