{
    "data_id": "43611",
    "name": "Wisconsin-breast-cancer-cytology-features",
    "exact_name": "Wisconsin-breast-cancer-cytology-features",
    "version": 1,
    "version_label": "v1.0",
    "description": "Context\nCytology features of breast cancer biopsy. It can be used to predict breast cancer from cytology features.\nThe data was obtained from https:\/\/archive.ics.uci.edu\/ml\/datasets\/Breast+Cancer+Wisconsin+(Original) \nData description can be found at https:\/\/archive.ics.uci.edu\/ml\/machine-learning-databases\/breast-cancer-wisconsin\/breast-cancer-wisconsin.names\nContent\nData contains cytology features of breast cancer biopsies - clump thickness, uniformity of cell size, uniformity of cell shape, marginal adhesion, single epithelial cell size, bare nuclei, bland chromatin, normal nuceloli, mitosis. The class variable denotes whether it was cancer or not. Cancer = 1 and not cancer = 0\nAttribute Information:\n\nSample code number: id number \nClump Thickness: 1 - 10 \nUniformity of Cell Size: 1 - 10 \nUniformity of Cell Shape: 1 - 10 \nMarginal Adhesion: 1 - 10 \nSingle Epithelial Cell Size: 1 - 10 \nBare Nuclei: 1 - 10 \nBland Chromatin: 1 - 10 \nNormal Nucleoli: 1 - 10 \nMitoses: 1 - 10 \nClass: (0 for benign, 1 for malignant)\n\nAcknowledgements\nData obtained from : UCI machine learning repository \nDua, D. and Karra Taniskidou, E. (2017). UCI Machine Learning Repository [http:\/\/archive.ics.uci.edu\/ml]. Irvine, CA: University of California, School of Information and Computer Science.\nPicture courtesy: Photo by Pablo Heimplatz on Unsplash",
    "format": "arff",
    "uploader": "Dustin Carrion",
    "uploader_id": 30123,
    "visibility": "public",
    "creator": null,
    "contributor": null,
    "date": "2022-03-24 00:40:12",
    "update_comment": null,
    "last_update": "2022-03-24 00:40:12",
    "licence": "CC0: Public Domain",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/www.openml.org\/data\/download\/22102436\/dataset",
    "default_target_attribute": null,
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
        "input": [
            "Wisconsin-breast-cancer-cytology-features",
            "Context Cytology features of breast cancer biopsy. It can be used to predict breast cancer from cytology features. The data was obtained from https:\/\/archive.ics.uci.edu\/ml\/datasets\/Breast+Cancer+Wisconsin+(Original) Data description can be found at https:\/\/archive.ics.uci.edu\/ml\/machine-learning-databases\/breast-cancer-wisconsin\/breast-cancer-wisconsin.names Content Data contains cytology features of breast cancer biopsies - clump thickness, uniformity of cell size, uniformity of cell shape, ma "
        ],
        "weight": 5
    },
    "qualities": {
        "NumberOfInstances": 699,
        "NumberOfFeatures": 11,
        "NumberOfClasses": null,
        "NumberOfMissingValues": 16,
        "NumberOfInstancesWithMissingValues": 16,
        "NumberOfNumericFeatures": 11,
        "NumberOfSymbolicFeatures": 0,
        "Dimensionality": 0.015736766809728183,
        "PercentageOfNumericFeatures": 100,
        "MajorityClassPercentage": null,
        "PercentageOfSymbolicFeatures": 0,
        "MajorityClassSize": null,
        "MinorityClassPercentage": null,
        "MinorityClassSize": null,
        "NumberOfBinaryFeatures": 0,
        "PercentageOfBinaryFeatures": 0,
        "PercentageOfInstancesWithMissingValues": 2.28898426323319,
        "AutoCorrelation": null,
        "PercentageOfMissingValues": 0.20808947847574458
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    "tags": [
        {
            "uploader": "38960",
            "tag": "Computer Systems"
        },
        {
            "uploader": "38960",
            "tag": "Machine Learning"
        }
    ],
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