{
    "data_id": "44191",
    "name": "Diabetes(scikit-learn)",
    "exact_name": "Diabetes(scikit-learn)",
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    "description": ".. _diabetes_dataset:\n\nDiabetes dataset\n----------------\n\nTen baseline variables, age, sex, body mass index, average blood\npressure, and six blood serum measurements were obtained for each of n =\n442 diabetes patients, as well as the response of interest, a\nquantitative measure of disease progression one year after baseline.\n\n**Data Set Characteristics:**\n\n  :Number of Instances: 442\n\n  :Number of Attributes: First 10 columns are numeric predictive values\n\n  :Target: Column 11 is a quantitative measure of disease progression one year after baseline\n\n  :Attribute Information:\n      - age     age in years\n      - sex\n      - bmi     body mass index\n      - bp      average blood pressure\n      - s1      tc, total serum cholesterol\n      - s2      ldl, low-density lipoproteins\n      - s3      hdl, high-density lipoproteins\n      - s4      tch, total cholesterol \/ HDL\n      - s5      ltg, possibly log of serum triglycerides level\n      - s6      glu, blood sugar level\n\nNote: Each of these 10 feature variables have been mean centered and scaled by the standard deviation times the square root of `n_samples` (i.e. the sum of squares of each column totals 1).\n\nSource URL:\nhttps:\/\/www4.stat.ncsu.edu\/~boos\/var.select\/diabetes.html\n\nFor more information see:\nBradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani (2004) \"Least Angle Regression,\" Annals of Statistics (with discussion), 407-499.\n(https:\/\/web.stanford.edu\/~hastie\/Papers\/LARS\/LeastAngle_2002.pdf)",
    "format": "arff",
    "uploader": "Ilin Tolovski",
    "uploader_id": 31897,
    "visibility": "public",
    "creator": "\"Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani\"",
    "contributor": null,
    "date": "2022-08-26 16:23:16",
    "update_comment": null,
    "last_update": "2022-08-26 16:23:16",
    "licence": "BSD (from scikit-learn)",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/api.openml.org\/data\/download\/22103384\/dataset",
    "default_target_attribute": "class",
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
        "input": [
            "Diabetes(scikit-learn)",
            ".. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442 diabetes patients, as well as the response of interest, a quantitative measure of disease progression one year after baseline. :Number of Instances: 442 :Number of Attributes: First 10 columns are numeric predictive values :Target: Column 11 is a quantitative measure of disease progression one year af "
        ],
        "weight": 5
    },
    "qualities": {
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        "NumberOfFeatures": 11,
        "NumberOfClasses": 0,
        "NumberOfMissingValues": 0,
        "NumberOfInstancesWithMissingValues": 0,
        "NumberOfNumericFeatures": 11,
        "NumberOfSymbolicFeatures": 0,
        "PercentageOfInstancesWithMissingValues": 0,
        "AutoCorrelation": -84.63718820861678,
        "PercentageOfMissingValues": 0,
        "Dimensionality": 0.024886877828054297,
        "PercentageOfNumericFeatures": 100,
        "MajorityClassPercentage": null,
        "PercentageOfSymbolicFeatures": 0,
        "MajorityClassSize": null,
        "MinorityClassPercentage": null,
        "MinorityClassSize": null,
        "NumberOfBinaryFeatures": 0,
        "PercentageOfBinaryFeatures": 0
    },
    "tags": [
        {
            "uploader": "38960",
            "tag": "Machine Learning"
        },
        {
            "uploader": "38960",
            "tag": "Meteorology"
        }
    ],
    "features": [
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            "min": "25",
            "max": "346",
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        },
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        },
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