{
    "data_id": "42900",
    "name": "breast-cancer-coimbra",
    "exact_name": "breast-cancer-coimbra",
    "version": 1,
    "version_label": "1",
    "description": "**Author**: Miguel Patricio, Jose Pereira, Joana Crisostomo, Paulo Matafome, Raquel Seica, Francisco Caramelo\n**Source**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/datasets\/Breast+Cancer+Coimbra) - 2018\n**Please cite**: [Paper](doi:10.1186\/s12885-017-3877-1  Heart failure clinical records dataset \n\n**Breast cancer coimbra dataset**\n\nThere are 10 predictors, all quantitative, and a binary dependent variable, indicating the presence or absence of breast cancer. The predictors are anthropometric data and parameters which can be gathered in routine blood analysis. Prediction models based on these predictors, if accurate, can potentially be used as a biomarker of breast cancer.\n\n### Attribute information\n\nQuantitative Attributes: \n- Age (years) \n- BMI (kg\/m2) \n- Glucose (mg\/dL) \n- Insulin (microgram\/mL) \n- HOMA \n- Leptin (ng\/mL) \n- Adiponectin (microg\/mL) \n- Resistin (ng\/mL) \n- MCP-1(pg\/dL) \n\nLabels: \n\n1. Healthy controls \n2. Patients",
    "format": "arff",
    "uploader": "Meilina Reksoprodjo",
    "uploader_id": 24140,
    "visibility": "public",
    "creator": "Miguel Patricio,Jose Pereira,Joana Crisostomo,Paulo Matafome,Raquel Seica,Francisco Caramelo",
    "contributor": null,
    "date": "2021-05-19 18:39:49",
    "update_comment": null,
    "last_update": "2021-05-19 18:39:49",
    "licence": "CC-BY",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/www.openml.org\/data\/download\/22045531\/dataset",
    "kaggle_url": null,
    "default_target_attribute": "Classification",
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
        "input": [
            "breast-cancer-coimbra",
            "There are 10 predictors, all quantitative, and a binary dependent variable, indicating the presence or absence of breast cancer. The predictors are anthropometric data and parameters which can be gathered in routine blood analysis. Prediction models based on these predictors, if accurate, can potentially be used as a biomarker of breast cancer. ### Attribute information Quantitative Attributes: - Age (years) - BMI (kg\/m2) - Glucose (mg\/dL) - Insulin (microgram\/mL) - HOMA - Leptin (ng\/mL) - Adipo "
        ],
        "weight": 5
    },
    "qualities": {
        "NumberOfInstances": 116,
        "NumberOfFeatures": 10,
        "NumberOfClasses": 0,
        "NumberOfMissingValues": 0,
        "NumberOfInstancesWithMissingValues": 0,
        "NumberOfNumericFeatures": 10,
        "NumberOfSymbolicFeatures": 0,
        "PercentageOfBinaryFeatures": 0,
        "PercentageOfInstancesWithMissingValues": 0,
        "PercentageOfMissingValues": 0,
        "AutoCorrelation": 0.991304347826087,
        "PercentageOfNumericFeatures": 100,
        "Dimensionality": 0.08620689655172414,
        "PercentageOfSymbolicFeatures": 0,
        "MajorityClassPercentage": null,
        "MajorityClassSize": null,
        "MinorityClassPercentage": null,
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    "tags": [],
    "features": [
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