DEVELOPMENT...      {
    "data_id": "44983",
    "name": "miami_housing",
    "exact_name": "miami_housing",
    "version": 2,
    "version_label": null,
    "description": "**Data description**\n\nThe dataset contains information on 13,932 single-family homes sold in Miami .\nContent.\n\nThe goal is to predict the sale price.\n\n**Attribute description**\n\nThe dataset contains the following columns:\n\n  * PARCELNO: unique identifier for each property. About 1% appear multiple times.\n  * SALE_PRC: sale price ($)\n  * LND_SQFOOT: land area (square feet)\n  * TOTLVGAREA: floor area (square feet)\n  * SPECFEATVAL: value of special features (e.g., swimming pools) ($)\n  * RAIL_DIST: distance to the nearest rail line (an indicator of noise) (feet)\n  * OCEAN_DIST: distance to the ocean (feet)\n  * WATER_DIST: distance to the nearest body of water (feet)\n  * CNTR_DIST: distance to the Miami central business district (feet)\n  * SUBCNTR_DI: distance to the nearest subcenter (feet)\n  * HWY_DIST: distance to the nearest highway (an indicator of noise) (feet)\n  * age: age of the structure\n  * avno60plus: dummy variable for airplane noise exceeding an acceptable level\n  * structure_quality: quality of the structure\n  * month_sold: sale month in 2016 (1 = jan)\n  * LATITUDE\n  * LONGITUDE",
    "format": "arff",
    "uploader": "Shirley ",
    "uploader_id": 30127,
    "visibility": "public",
    "creator": null,
    "contributor": null,
    "date": "2022-12-22 16:15:59",
    "update_comment": null,
    "last_update": "2022-12-22 16:15:59",
    "licence": "CC0: Public Domain",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/api.openml.org\/data\/download\/22111847\/file22f16556075ab.arff",
    "default_target_attribute": "SALE_PRC",
    "row_id_attribute": null,
    "ignore_attribute": "\"PARCELNO\"",
    "runs": 0,
    "suggest": {
        "input": [
            "miami_housing",
            "The dataset contains information on 13,932 single-family homes sold in Miami . Content. The goal is to predict the sale price. The dataset contains the following columns: * PARCELNO: unique identifier for each property. About 1% appear multiple times. * SALE_PRC: sale price ($) * LND_SQFOOT: land area (square feet) * TOTLVGAREA: floor area (square feet) * SPECFEATVAL: value of special features (e.g., swimming pools) ($) * RAIL_DIST: distance to the nearest rail line (an indicator of noise) (feet "
        ],
        "weight": 5
    },
    "qualities": {
        "NumberOfInstances": 13932,
        "NumberOfFeatures": 16,
        "NumberOfClasses": 0,
        "NumberOfMissingValues": 0,
        "NumberOfInstancesWithMissingValues": 0,
        "NumberOfNumericFeatures": 16,
        "NumberOfSymbolicFeatures": 0,
        "PercentageOfSymbolicFeatures": 0,
        "AutoCorrelation": -123005.68394228698,
        "PercentageOfNumericFeatures": 100,
        "PercentageOfMissingValues": 0,
        "PercentageOfInstancesWithMissingValues": 0,
        "PercentageOfBinaryFeatures": 0,
        "NumberOfBinaryFeatures": 0,
        "MinorityClassSize": null,
        "MinorityClassPercentage": null,
        "MajorityClassSize": null,
        "MajorityClassPercentage": null,
        "Dimensionality": 0.0011484352569623888
    },
    "tags": [
        {
            "tag": "study_353",
            "uploader": "0"
        }
    ],
    "features": [
        {
            "name": "SALE_PRC",
            "index": "3",
            "type": "numeric",
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            "target": "1",
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            "max": "2650000",
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            "stdev": "317215"
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            "max": "75745",
            "mean": "31691",
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            "name": "structure_quality",
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            "type": "numeric",
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        },
        {
            "name": "month_sold",
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            "name": "avno60plus",
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        },
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        },
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            "name": "SPEC_FEAT_VAL",
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            "name": "TOT_LVG_AREA",
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        },
        {
            "name": "LND_SQFOOT",
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        },
        {
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            "ignore": "1",
            "min": "0",
            "max": "0",
            "mean": "0",
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        },
        {
            "name": "LONGITUDE",
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        }
    ],
    "nr_of_issues": 0,
    "nr_of_downvotes": 0,
    "nr_of_likes": 0,
    "nr_of_downloads": 0,
    "total_downloads": 0,
    "reach": 0,
    "reuse": 0,
    "impact_of_reuse": 0,
    "reach_of_reuse": 0,
    "impact": 0
}