{
    "data_id": "1464",
    "name": "blood-transfusion-service-center",
    "exact_name": "blood-transfusion-service-center",
    "version": 1,
    "version_label": null,
    "description": "**Author**: Prof. I-Cheng Yeh  \n**Source**: [UCI](https:\/\/archive.ics.uci.edu\/ml\/datasets\/Blood+Transfusion+Service+Center)  \n**Please cite**: Yeh, I-Cheng, Yang, King-Jang, and Ting, Tao-Ming, \"Knowledge discovery on RFM model using Bernoulli sequence\", Expert Systems with Applications, 2008.   \n\n**Blood Transfusion Service Center Data Set**  \nData taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem.\n\nTo demonstrate the RFMTC marketing model (a modified version of RFM), this study adopted the donor database of Blood Transfusion Service Center in Hsin-Chu City in Taiwan. The center passes their blood transfusion service bus to one university in Hsin-Chu City to gather blood donated about every three months. To build an FRMTC model, we selected 748 donors at random from the donor database. \n\n### Attribute Information  \n* V1: Recency - months since last donation\n* V2: Frequency - total number of donation\n* V3: Monetary - total blood donated in c.c.\n* V4: Time - months since first donation), and a binary variable representing whether he\/she donated blood in March 2007 (1 stand for donating blood; 0 stands for not donating blood).\n\nThe target attribute is a binary variable representing whether he\/she donated blood in March 2007 (2 stands for donating blood; 1 stands for not donating blood).",
    "format": "ARFF",
    "uploader": "Rafael Gomes Mantovani",
    "uploader_id": 64,
    "visibility": "public",
    "creator": " ",
    "contributor": null,
    "date": "2015-05-21 22:49:48",
    "update_comment": null,
    "last_update": "2015-11-09 21:02:59",
    "licence": "Public",
    "status": "active",
    "error_message": null,
    "url": "https:\/\/www.openml.org\/data\/download\/1586225\/php0iVrYT",
    "default_target_attribute": "Class",
    "row_id_attribute": null,
    "ignore_attribute": null,
    "runs": 468690,
    "suggest": {
        "input": [
            "blood-transfusion-service-center",
            "Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem. To demonstrate the RFMTC marketing model (a modified version of RFM), this study adopted the donor database of Blood Transfusion Service Center in Hsin-Chu City in Taiwan. The center passes their blood transfusion service bus to one university in Hsin-Chu City to gather blood donated about every three months. To build an FRMTC model, we selected 748 donors at random from the donor "
        ],
        "weight": 5
    },
    "qualities": {
        "NumberOfInstances": 748,
        "NumberOfFeatures": 5,
        "NumberOfClasses": 2,
        "NumberOfMissingValues": 0,
        "NumberOfInstancesWithMissingValues": 0,
        "NumberOfNumericFeatures": 4,
        "NumberOfSymbolicFeatures": 1,
        "RandomTreeDepth3Kappa": 0.13567374666781304,
        "J48.001.AUC": 0.6960230632761679,
        "MeanNoiseToSignalRatio": null,
        "NumberOfBinaryFeatures": 1,
        "Quartile1MutualInformation": null,
        "REPTreeDepth1ErrRate": 0.23796791443850268,
        "CfsSubsetEval_NaiveBayesKappa": 0.02063078703703703,
        "StdvNominalAttDistinctValues": 0,
        "J48.001.ErrRate": 0.22459893048128343,
        "MeanNominalAttDistinctValues": 2,
        "Quartile1SkewnessOfNumericAtts": 1.0322036011463176,
        "REPTreeDepth1Kappa": 0.17490456596103332,
        "CfsSubsetEval_kNN1NAUC": 0.635053222945003,
        "kNN1NAUC": 0.6044253893159865,
        "J48.001.Kappa": 0.32603938730853393,
        "MeanSkewnessOfNumericAtts": 2.263111192925173,
        "Quartile1StdDevOfNumericAtts": 6.403329251142325,
        "REPTreeDepth2AUC": 0.7011186674551547,
        "CfsSubsetEval_kNN1NErrRate": 0.24197860962566844,
        "kNN1NErrRate": 0.28609625668449196,
        "MajorityClassPercentage": 76.20320855614973,
        "MeanStdDevOfNumericAtts": 374.5345494748768,
        "Quartile2AttributeEntropy": null,
        "REPTreeDepth2ErrRate": 0.23796791443850268,
        "CfsSubsetEval_kNN1NKappa": 0.02063078703703703,
        "kNN1NKappa": 0.1486618729523889,
        "MajorityClassSize": 570,
        "MinAttributeEntropy": null,
        "Quartile2KurtosisOfNumericAtts": 12.633750101130904,
        "REPTreeDepth2Kappa": 0.17490456596103332,
        "ClassEntropy": 0.7916446298452329,
        "MaxAttributeEntropy": null,
        "MinKurtosisOfNumericAtts": -0.24563117940242574,
        "Quartile2MeansOfNumericAtts": 21.89438502673798,
        "REPTreeDepth3AUC": 0.7011186674551547,
        "DecisionStumpAUC": 0.6777646363098758,
        "MaxKurtosisOfNumericAtts": 15.876151978542005,
        "MinMeansOfNumericAtts": 5.514705882352952,
        "Quartile2MutualInformation": null,
        "REPTreeDepth3ErrRate": 0.23796791443850268,
        "DecisionStumpErrRate": 0.23796791443850268,
        "MaxMeansOfNumericAtts": 1378.6764705882335,
        "MinMutualInformation": null,
        "Quartile2SkewnessOfNumericAtts": 2.5458645034443492,
        "REPTreeDepth3Kappa": 0.17490456596103332,
        "DecisionStumpKappa": 0,
        "Dimensionality": 0.0066844919786096255,
        "MaxMutualInformation": null,
        "MinNominalAttDistinctValues": 2,
        "PercentageOfBinaryFeatures": 20,
        "Quartile2StdDevOfNumericAtts": 16.23605500195668,
        "RandomTreeDepth1AUC": 0.5678050463236743,
        "EquivalentNumberOfAtts": null,
        "MaxNominalAttDistinctValues": 2,
        "MinSkewnessOfNumericAtts": 0.7494502906271294,
        "PercentageOfInstancesWithMissingValues": 0,
        "Quartile3AttributeEntropy": null,
        "RandomTreeDepth1ErrRate": 0.2874331550802139,
        "J48.00001.AUC": 0.6960230632761679,
        "MaxSkewnessOfNumericAtts": 3.2112654741848643,
        "MinStdDevOfNumericAtts": 5.8393071230900295,
        "PercentageOfMissingValues": 0,
        "Quartile3KurtosisOfNumericAtts": 15.876151978541927,
        "AutoCorrelation": 0.7309236947791165,
        "RandomTreeDepth1Kappa": 0.13567374666781304,
        "J48.00001.ErrRate": 0.22459893048128343,
        "MaxStdDevOfNumericAtts": 1459.826780772504,
        "MinorityClassPercentage": 23.796791443850267,
        "PercentageOfNumericFeatures": 80,
        "Quartile3MeansOfNumericAtts": 1042.5778743315495,
        "CfsSubsetEval_DecisionStumpAUC": 0.635053222945003,
        "RandomTreeDepth2AUC": 0.5678050463236743,
        "RandomTreeDepth2ErrRate": 0.2874331550802139,
        "J48.00001.Kappa": 0.32603938730853393,
        "MeanAttributeEntropy": null,
        "MinorityClassSize": 178,
        "PercentageOfSymbolicFeatures": 20,
        "Quartile3MutualInformation": null,
        "CfsSubsetEval_DecisionStumpErrRate": 0.24197860962566844,
        "RandomTreeDepth2Kappa": 0.13567374666781304,
        "J48.0001.AUC": 0.6960230632761679,
        "MeanKurtosisOfNumericAtts": 10.224505250350347,
        "NaiveBayesAUC": 0.6667800118273212,
        "Quartile1AttributeEntropy": null,
        "Quartile3SkewnessOfNumericAtts": 3.2112654741848523,
        "CfsSubsetEval_DecisionStumpKappa": 0.02063078703703703,
        "RandomTreeDepth3AUC": 0.5678050463236743,
        "J48.0001.ErrRate": 0.22459893048128343,
        "MeanMeansOfNumericAtts": 356.99498663101565,
        "NaiveBayesErrRate": 0.2446524064171123,
        "Quartile1KurtosisOfNumericAtts": 2.1636136713782106,
        "Quartile3StdDevOfNumericAtts": 1100.9642641715316,
        "CfsSubsetEval_NaiveBayesAUC": 0.635053222945003,
        "RandomTreeDepth3ErrRate": 0.2874331550802139,
        "J48.0001.Kappa": 0.32603938730853393,
        "MeanMutualInformation": null,
        "NaiveBayesKappa": 0.14966206142530555,
        "Quartile1MeansOfNumericAtts": 6.512700534759367,
        "REPTreeDepth1AUC": 0.7011186674551547,
        "CfsSubsetEval_NaiveBayesErrRate": 0.24197860962566844
    },
    "tags": [
        {
            "tag": "Chemistry",
            "uploader": "38960"
        },
        {
            "tag": "Life Science",
            "uploader": "38960"
        },
        {
            "tag": "OpenML-CC18",
            "uploader": "1"
        },
        {
            "tag": "OpenML100",
            "uploader": "348"
        },
        {
            "tag": "study_123",
            "uploader": "3886"
        },
        {
            "tag": "study_135",
            "uploader": "5824"
        },
        {
            "tag": "study_14",
            "uploader": "64"
        },
        {
            "tag": "study_218",
            "uploader": "869"
        },
        {
            "tag": "study_34",
            "uploader": "1"
        },
        {
            "tag": "study_50",
            "uploader": "64"
        },
        {
            "tag": "study_52",
            "uploader": "64"
        },
        {
            "tag": "study_7",
            "uploader": "64"
        },
        {
            "tag": "study_98",
            "uploader": "1935"
        },
        {
            "tag": "study_99",
            "uploader": "1"
        },
        {
            "tag": "uci",
            "uploader": "2"
        },
        {
            "tag": "study_225",
            "uploader": "0"
        },
        {
            "tag": "study_236",
            "uploader": "0"
        },
        {
            "tag": "study_271",
            "uploader": "0"
        },
        {
            "tag": "study_240",
            "uploader": "0"
        },
        {
            "tag": "study_253",
            "uploader": "0"
        },
        {
            "tag": "study_338",
            "uploader": "0"
        },
        {
            "tag": "study_339",
            "uploader": "0"
        },
        {
            "tag": "study_342",
            "uploader": "0"
        },
        {
            "tag": "study_343",
            "uploader": "0"
        },
        {
            "tag": "study_275",
            "uploader": "0"
        }
    ],
    "features": [
        {
            "name": "Class",
            "index": "4",
            "type": "nominal",
            "distinct": "2",
            "missing": "0",
            "target": "1",
            "distr": [
                [
                    "1",
                    "2"
                ],
                [
                    [
                        "570",
                        "0"
                    ],
                    [
                        "0",
                        "178"
                    ]
                ]
            ]
        },
        {
            "name": "V1",
            "index": "0",
            "type": "numeric",
            "distinct": "31",
            "missing": "0",
            "min": "0",
            "max": "74",
            "mean": "10",
            "stdev": "8"
        },
        {
            "name": "V2",
            "index": "1",
            "type": "numeric",
            "distinct": "33",
            "missing": "0",
            "min": "1",
            "max": "50",
            "mean": "6",
            "stdev": "6"
        },
        {
            "name": "V3",
            "index": "2",
            "type": "numeric",
            "distinct": "33",
            "missing": "0",
            "min": "250",
            "max": "12500",
            "mean": "1379",
            "stdev": "1460"
        },
        {
            "name": "V4",
            "index": "3",
            "type": "numeric",
            "distinct": "78",
            "missing": "0",
            "min": "2",
            "max": "98",
            "mean": "34",
            "stdev": "24"
        }
    ],
    "nr_of_issues": 0,
    "nr_of_downvotes": 0,
    "nr_of_likes": 6,
    "nr_of_downloads": 101,
    "total_downloads": 126,
    "reach": 107,
    "reuse": 33,
    "impact_of_reuse": 0,
    "reach_of_reuse": 27,
    "impact": 46
}