{
    "data_id": "43955",
    "name": "poker",
    "exact_name": "poker",
    "version": 3,
    "version_label": null,
    "description": "Dataset used in the tabular data benchmark https:\/\/github.com\/LeoGrin\/tabular-benchmark, transformed in the same way. This dataset belongs to the \"classification on numerical features\" benchmark. Original description: \n \n**Author**: UCI  \n**Source**: [original](http:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvmtools\/datasets) -   \n**Please cite**:   \n\nThis is the poker dataset, retrieved 2013-11-14 from the libSVM site. Additional to the preprocessing done there (see LibSVM site for details), this dataset was created as follows:    \n\n-join test and train datasets (non-scaled versions)   \n-relabel classes 0=positive class and 1,2,...9=negative class   \n-normalize each file columnwise according to the following rules:    \n-If a column only contains one value (constant feature), it will set to zero and thus removed by sparsity.    \n-If a column contains two values (binary feature), the value occuring more often will be set to zero, the other to one.   \n-If a column contains more than two values (multinary\/real feature), the column is divided by its std deviation.   \n\nNOTE: please keep in mind that poker has a mild redundancy, e.g. some duplicated data points, roughly 0.2%, within each file (train,test). these duplicated points have not been removed!",
    "format": "arff",
    "uploader": "Leo Grin",
    "uploader_id": 26324,
    "visibility": "public",
    "creator": "\"UCI\"",
    "contributor": "\"Leo Grin\"",
    "date": "2022-06-15 20:37:43",
    "update_comment": null,
    "last_update": "2022-06-15 20:37:43",
    "licence": "Public",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/old.openml.org\/data\/download\/22103041\/dataset",
    "kaggle_url": null,
    "default_target_attribute": "Y",
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 0,
    "suggest": {
        "input": [
            "poker",
            "Dataset used in the tabular data benchmark https:\/\/github.com\/LeoGrin\/tabular-benchmark, transformed in the same way. This dataset belongs to the \"classification on numerical features\" benchmark. Original description: This is the poker dataset, retrieved 2013-11-14 from the libSVM site. Additional to the preprocessing done there (see LibSVM site for details), this dataset was created as follows: -join test and train datasets (non-scaled versions) -relabel classes 0=positive class and 1,2,...9=ne "
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    "qualities": {
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        "NumberOfFeatures": 6,
        "NumberOfClasses": 0,
        "NumberOfMissingValues": 0,
        "NumberOfInstancesWithMissingValues": 0,
        "NumberOfNumericFeatures": 6,
        "NumberOfSymbolicFeatures": 0,
        "PercentageOfBinaryFeatures": 0,
        "PercentageOfInstancesWithMissingValues": 0,
        "PercentageOfMissingValues": 0,
        "AutoCorrelation": 0.9999990221148721,
        "PercentageOfNumericFeatures": 100,
        "Dimensionality": 5.867305029453872e-6,
        "PercentageOfSymbolicFeatures": 0,
        "MajorityClassPercentage": null,
        "MajorityClassSize": null,
        "MinorityClassPercentage": null,
        "MinorityClassSize": null,
        "NumberOfBinaryFeatures": 0
    },
    "tags": [],
    "features": [
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            "name": "Y",
            "index": "5",
            "type": "numeric",
            "distinct": "2",
            "missing": "0",
            "target": "1",
            "min": "0",
            "max": "1",
            "mean": "1",
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        },
        {
            "name": "X2",
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            "missing": "0",
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            "mean": "2",
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            "name": "X6",
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