{
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    "name": "GDP-per-capita-all-countries",
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    "description": "Gross Domestic Product (GDP) is the monetary value of all finished goods and services made within a country during a specific period. GDP provides an economic snapshot of a country, used to estimate the size of an economy and growth rate.\nThis dataset contains the GDP based on Purchasing Power Parity (PPP). \nGDP comparisons using PPP are arguably more useful than those using nominal GDP when assessing a nation's domestic market because PPP takes into account the relative cost of local goods, services and inflation rates of the country, rather than using international market exchange rates which may distort the real differences in per capita income\nAcknowledgement\nThanks to World Databank",
    "format": "arff",
    "uploader": "Elif Ceren Gok",
    "uploader_id": 30125,
    "visibility": "public",
    "creator": null,
    "contributor": null,
    "date": "2022-03-24 15:11:28",
    "update_comment": null,
    "last_update": "2022-03-24 15:11:28",
    "licence": "CC0: Public Domain",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/www.openml.org\/data\/download\/22102634\/dataset",
    "default_target_attribute": null,
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
        "input": [
            "GDP-per-capita-all-countries",
            "Gross Domestic Product (GDP) is the monetary value of all finished goods and services made within a country during a specific period. GDP provides an economic snapshot of a country, used to estimate the size of an economy and growth rate. This dataset contains the GDP based on Purchasing Power Parity (PPP). GDP comparisons using PPP are arguably more useful than those using nominal GDP when assessing a nation's domestic market because PPP takes into account the relative cost of local goods, serv "
        ],
        "weight": 5
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        "NumberOfFeatures": 32,
        "NumberOfClasses": null,
        "NumberOfMissingValues": 1074,
        "NumberOfInstancesWithMissingValues": 260,
        "NumberOfNumericFeatures": 30,
        "NumberOfSymbolicFeatures": 0,
        "Dimensionality": 0.12307692307692308,
        "PercentageOfNumericFeatures": 93.75,
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        "AutoCorrelation": null,
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        {
            "uploader": "38960",
            "tag": "Machine Learning"
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        {
            "uploader": "38960",
            "tag": "Social Media"
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