{
   "name": "blood-transfusion-service-center",
   "title": "Blood transfusion service center",
   "resources": [
      {
         "path": "blood-transfusion-service-center.arff",
         "pathType": "local",
         "name": "blood-transfusion-service-center",
         "format": "arff",
         "encoding": "ISO-8859-1"
      },
      {
         "path": "blood-transfusion-service-center.csv",
         "pathType": "local",
         "name": "blood-transfusion-service-center",
         "format": "csv",
         "mediatype": "text/csv",
         "encoding": "ISO-8859-2",
         "dialect": {
            "delimiter": ",",
            "quoteChar": "\""
         },
         "schema": {
            "fields": [
               {
                  "name": "V1",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "V2",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "V3",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "V4",
                  "type": "number",
                  "format": "default"
               },
               {
                  "name": "Class",
                  "type": "number",
                  "format": "default"
               }
            ],
            "missingValues": [
               ""
            ]
         }
      }
   ],
   "readme": "The resources for this dataset can be found at https://www.openml.org/d/1464\n\nAuthor: Prof. I-Cheng Yeh  \nSource: [UCI](https://archive.ics.uci.edu/ml/datasets/Blood+Transfusion+Service+Center)  \nPlease 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\nBlood 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).",
   "description": "The resources for this dataset can be found at https://www.openml.org/d/1464\n\nAuthor: Prof. I-Cheng ",
   "licenses": [
      {
         "name": "ODC-PDDL",
         "path": "http://opendatacommons.org/licenses/pddl/",
         "title": "Open Data Commons Public Domain Dedication and License"
      }
   ]
}