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-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.
-	
-
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-
-Data Set Characteristics: Multivariate
-Number of Instances: 748
-Area: Business
-Attribute Characteristics: Real
-Number of Attributes: 5
-Date Donated: 2008-10-03
-Associated Tasks: Classification
-Missing Values? N/A
-
-----------------------------------------------------
-
-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
-
-Date Donated: October 3, 2008 
-
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-
-Data Set Information:
-
-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 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).
-
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-
-Attribute Information:
-
-Given 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.
-
-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).
-
-
-Table 1 shows the descriptive statistics of the data. We selected 500 data at 
-random as the training set, and the rest 248 as the testing set.
-
-Table 1. Descriptive statistics of the data
-
-Variable Data Type Measurement Description min max mean std
-Recency quantitative Months Input 0.03 74.4 9.74 8.07
-Frequency quantitative Times Input 1 50 5.51 5.84
-Monetary quantitative c.c. blood Input 250 12500 1378.68 1459.83
-Time quantitative Months Input 2.27 98.3 34.42 24.32
-Whether he/she donated blood in March 2007 binary 1=yes 0=no Output 0 1 1 (24%) 0 (76%)
-
-
-----------------------------------------------------
-
-Citation Request:
-
-NOTE: Reuse of this database is unlimited with retention of copyright notice for 
-Prof. I-Cheng Yeh and the following published paper:
-
-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).
-
-