{ "data_id": "64", "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\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 (doi:10.1016\/j.eswa.2008.07.018). \n\nTitle: Blood Transfusion Service Center Data Set\n\nAbstract: Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem.\n\n-----------------------------------------------------\nDate Donated: 2008-10-03\n-----------------------------------------------------\n \nSource:\n \nOriginal Owner and Donor\nProf. I-Cheng Yeh, Department of Information Management, Chung-Hua University, Hsin Chu, Taiwan 30067, R.O.C.\ne-mail:icyeh 'at' chu.edu.tw, TEL:886-3-5186511\nDate Donated: October 3, 2008 \n\n-----------------------------------------------------\n \nData Set Information:\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 a FRMTC model, we selected 748 donors at random from the donor database. These 748 donor data, each one included R (Recency - months since last donation), F (Frequency - total number of donation), M (Monetary - total blood donated in c.c.), T (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\n-----------------------------------------------------\n \nAttribute Information:\n \nGiven is the variable name, variable type, the measurement unit and a brief description. The \"Blood Transfusion Service Center\" is a classification problem. The order of this listing corresponds to the order of numerals along the rows of the database.\n\nR (Recency - months since last donation),\nF (Frequency - total number of donation),\nM (Monetary - total blood donated in c.c.),\nT (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 \nCitation Request:\n \nNOTE: Reuse of this database is unlimited with retention of copyright notice for Prof. I-Cheng Yeh and the following published paper:\n\nYeh, I-Cheng, Yang, King-Jang, and Ting, Tao-Ming, \"Knowledge discovery on RFM model using Bernoulli sequence, \"Expert Systems with Applications, 2008 (doi:10.1016\/j.eswa.2008.07.018).", "format": "ARFF", "uploader": "Rafael Gomes Mantovani", "uploader_id": 64, "visibility": "public", "creator": null, "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": 0, "suggest": { "input": [ "blood-transfusion-service-center", "Title: Blood Transfusion Service Center Data Set Abstract: Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem. ----------------------------------------------------- Date Donated: 2008-10-03 ----------------------------------------------------- Source: Original Owner and Donor Prof. I-Cheng Yeh, Department of Information Management, Chung-Hua University, Hsin Chu, Taiwan 30067, R.O.C. e-mail:icyeh 'at' chu.edu.tw, TEL:886-3-5186511 " ], "weight": 5 }, "qualities": { "NumberOfInstances": 748, "NumberOfFeatures": 5, "NumberOfClasses": 2, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 4, "NumberOfSymbolicFeatures": 1, "AutoCorrelation": 0.7309236947791165, "CfsSubsetEval_DecisionStumpAUC": 0.635053222945003, "CfsSubsetEval_DecisionStumpErrRate": 0.24197860962566844, "CfsSubsetEval_DecisionStumpKappa": 0.02063078703703703, "CfsSubsetEval_NaiveBayesAUC": 0.635053222945003, "CfsSubsetEval_NaiveBayesErrRate": 0.24197860962566844, "CfsSubsetEval_NaiveBayesKappa": 0.02063078703703703, "CfsSubsetEval_kNN1NAUC": 0.635053222945003, "CfsSubsetEval_kNN1NErrRate": 0.24197860962566844, "CfsSubsetEval_kNN1NKappa": 0.02063078703703703, "ClassEntropy": 0.7916446298452329, "DecisionStumpAUC": 0.6777646363098758, "DecisionStumpErrRate": 0.23796791443850268, "DecisionStumpKappa": 0, "Dimensionality": 0.0066844919786096255, "EquivalentNumberOfAtts": null, "J48.00001.AUC": 0.6960230632761679, "J48.00001.ErrRate": 0.22459893048128343, "J48.00001.Kappa": 0.32603938730853393, "J48.0001.AUC": 0.6960230632761679, "J48.0001.ErrRate": 0.22459893048128343, "J48.0001.Kappa": 0.32603938730853393, "J48.001.AUC": 0.6960230632761679, "J48.001.ErrRate": 0.22459893048128343, "J48.001.Kappa": 0.32603938730853393, "MajorityClassPercentage": 76.20320855614973, "MajorityClassSize": 570, "MaxAttributeEntropy": null, "MaxKurtosisOfNumericAtts": 15.876151978542005, "MaxMeansOfNumericAtts": 1378.6764705882335, "MaxMutualInformation": null, "MaxNominalAttDistinctValues": 2, "MaxSkewnessOfNumericAtts": 3.2112654741848643, "MaxStdDevOfNumericAtts": 1459.826780772504, "MeanAttributeEntropy": null, "MeanKurtosisOfNumericAtts": 10.224505250350347, "MeanMeansOfNumericAtts": 356.99498663101565, "MeanMutualInformation": null, "MeanNoiseToSignalRatio": null, "MeanNominalAttDistinctValues": 2, "MeanSkewnessOfNumericAtts": 2.263111192925173, "MeanStdDevOfNumericAtts": 374.5345494748768, "MinAttributeEntropy": null, "MinKurtosisOfNumericAtts": -0.24563117940242574, "MinMeansOfNumericAtts": 5.514705882352952, "MinMutualInformation": null, "MinNominalAttDistinctValues": 2, "MinSkewnessOfNumericAtts": 0.7494502906271294, "MinStdDevOfNumericAtts": 5.8393071230900295, "MinorityClassPercentage": 23.796791443850267, "MinorityClassSize": 178, "NaiveBayesAUC": 0.6667800118273212, "NaiveBayesErrRate": 0.2446524064171123, "NaiveBayesKappa": 0.14966206142530555, "NumberOfBinaryFeatures": 1, "PercentageOfBinaryFeatures": 20, "PercentageOfInstancesWithMissingValues": 0, "PercentageOfMissingValues": 0, "PercentageOfNumericFeatures": 80, "PercentageOfSymbolicFeatures": 20, "Quartile1AttributeEntropy": null, "Quartile1KurtosisOfNumericAtts": 2.1636136713782106, "Quartile1MeansOfNumericAtts": 6.512700534759367, "Quartile1MutualInformation": null, "Quartile1SkewnessOfNumericAtts": 1.0322036011463176, "Quartile1StdDevOfNumericAtts": 6.403329251142325, "Quartile2AttributeEntropy": null, "Quartile2KurtosisOfNumericAtts": 12.633750101130904, "Quartile2MeansOfNumericAtts": 21.89438502673798, "Quartile2MutualInformation": null, "Quartile2SkewnessOfNumericAtts": 2.5458645034443492, "Quartile2StdDevOfNumericAtts": 16.23605500195668, "Quartile3AttributeEntropy": null, "Quartile3KurtosisOfNumericAtts": 15.876151978541927, "Quartile3MeansOfNumericAtts": 1042.5778743315495, "Quartile3MutualInformation": null, "Quartile3SkewnessOfNumericAtts": 3.2112654741848523, "Quartile3StdDevOfNumericAtts": 1100.9642641715316, "REPTreeDepth1AUC": 0.7011186674551547, "REPTreeDepth1ErrRate": 0.23796791443850268, "REPTreeDepth1Kappa": 0.17490456596103332, "REPTreeDepth2AUC": 0.7011186674551547, "REPTreeDepth2ErrRate": 0.23796791443850268, "REPTreeDepth2Kappa": 0.17490456596103332, "REPTreeDepth3AUC": 0.7011186674551547, "REPTreeDepth3ErrRate": 0.23796791443850268, "REPTreeDepth3Kappa": 0.17490456596103332, "RandomTreeDepth1AUC": 0.5678050463236743, "RandomTreeDepth1ErrRate": 0.2874331550802139, "RandomTreeDepth1Kappa": 0.13567374666781304, "RandomTreeDepth2AUC": 0.5678050463236743, "RandomTreeDepth2ErrRate": 0.2874331550802139, "RandomTreeDepth2Kappa": 0.13567374666781304, "RandomTreeDepth3AUC": 0.5678050463236743, "RandomTreeDepth3ErrRate": 0.2874331550802139, "RandomTreeDepth3Kappa": 0.13567374666781304, "StdvNominalAttDistinctValues": 0, "kNN1NAUC": 0.6044253893159865, "kNN1NErrRate": 0.28609625668449196, "kNN1NKappa": 0.1486618729523889 }, "tags": [ { "tag": "study_14", "uploader": "1" }, { "tag": "study_1", "uploader": "0" }, { "tag": "study_15", "uploader": "0" }, { "tag": "study_17", "uploader": "0" }, { "tag": "study_29", "uploader": "0" }, { "tag": "study_32", "uploader": "0" }, { "tag": "study_48", "uploader": "0" }, { "tag": "study_69", "uploader": "0" }, { "tag": "study_90", "uploader": "0" }, { "tag": "study_92", "uploader": "0" }, { "tag": "study_94", "uploader": "0" }, { "tag": "study_96", "uploader": "0" }, { "tag": "study_98", "uploader": "0" }, { "tag": "study_127", "uploader": "0" }, { "tag": "study_15", "uploader": "0" }, { "tag": "study_17", "uploader": "0" }, { "tag": "study_29", "uploader": "0" }, { "tag": "study_32", "uploader": "0" }, { "tag": "study_38", "uploader": "0" }, { "tag": "study_48", "uploader": "0" }, { "tag": "study_69", "uploader": "0" }, { "tag": "study_90", "uploader": "0" }, { "tag": "study_92", "uploader": "0" }, { "tag": "study_94", "uploader": "0" }, { "tag": "study_96", "uploader": "0" }, { "tag": "study_98", "uploader": "0" }, { "tag": "study_127", "uploader": "0" }, { "tag": "study_15", "uploader": "0" }, { "tag": "study_17", "uploader": "0" }, { "tag": "study_29", "uploader": "0" }, { "tag": "study_32", "uploader": "0" }, { "tag": "study_48", "uploader": "0" }, { "tag": "study_69", "uploader": "0" }, { "tag": "study_90", "uploader": "0" }, { "tag": "study_92", "uploader": "0" }, { "tag": "study_94", "uploader": "0" }, { "tag": "study_96", "uploader": "0" }, { "tag": "study_98", "uploader": "0" }, { "tag": "study_127", "uploader": "0" }, { "tag": "study_15", "uploader": "0" }, { "tag": "study_17", "uploader": "0" }, { "tag": "study_29", "uploader": "0" }, { "tag": "study_32", "uploader": "0" }, { "tag": "study_40", "uploader": "0" }, { "tag": "study_48", "uploader": "0" }, { "tag": "study_69", "uploader": "0" }, { "tag": "study_90", "uploader": "0" }, { "tag": "study_92", "uploader": "0" }, { "tag": "study_94", "uploader": "0" }, { "tag": "study_96", "uploader": "0" }, { "tag": "study_98", "uploader": "0" }, { "tag": "study_127", "uploader": "0" }, { "tag": "study_15", "uploader": "0" }, { "tag": "study_17", "uploader": "0" }, { "tag": "study_29", "uploader": "0" }, { "tag": "study_32", "uploader": "0" }, { "tag": "study_48", "uploader": "0" }, { "tag": "study_69", "uploader": "0" }, { "tag": "study_90", "uploader": "0" }, { "tag": "study_92", "uploader": "0" }, { "tag": "study_94", "uploader": "0" }, { "tag": "study_96", "uploader": "0" }, { "tag": "study_98", "uploader": "0" }, { "tag": "study_127", "uploader": "0" }, { "tag": "study_15", "uploader": "0" }, { "tag": "study_17", "uploader": "0" }, { "tag": "study_29", "uploader": "0" }, { "tag": "study_32", "uploader": "0" }, { "tag": "study_48", "uploader": "0" }, { "tag": "study_69", "uploader": "0" }, { "tag": "study_90", "uploader": "0" }, { "tag": "study_92", "uploader": "0" }, { "tag": "study_94", "uploader": "0" }, { "tag": "study_96", "uploader": "0" }, { "tag": "study_98", "uploader": "0" }, { "tag": "study_127", "uploader": "0" }, { "tag": "study_40", "uploader": "0" }, { "tag": "study_2", "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": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 11, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 11 }