Blood Transfusion Service Center
Donated on 10/2/2008
Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem.
Dataset Characteristics
Multivariate
Subject Area
Business
Associated Tasks
Classification
Feature Type
Real
# Instances
748
# Features
4
Dataset Information
Additional 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).
Has Missing Values?
No
Introductory Paper
By I. Yeh, K. Yang, Tao-Ming Ting. 2009
Published in Expert systems with applications
Variables Table
Variable Name | Role | Type | Description | Units | Missing Values |
---|---|---|---|---|---|
Recency | Feature | Integer | months since last donation | no | |
Frequency | Feature | Integer | total number of donations | no | |
Monetary | Feature | Integer | total blood donated in c.c. | no | |
Time | Feature | Integer | months since first donation | no | |
Donated_Blood | Target | Binary | whether he/she donated blood in March 2007 (1 stand for donating blood; 0 stands for not donating blood) | no |
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Additional Variable 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%)
Dataset Files
File | Size |
---|---|
transfusion.data | 12.5 KB |
transfusion.names | 3.1 KB |
Papers Citing this Dataset
Sort by Year, desc
By Erdem Biyik, Kenneth Wang, Nima Anari, Dorsa Sadigh. 2019
Published in ArXiv.
By Onesfole Kurama, Pasi Luukka, Mikael Collan. 2016
Published in Adv. Fuzzy Systems.
By Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zolt'an Szab'o. 2015
Published in ArXiv.
By T. Santhanam, Shyam Sundaram. 2010
Published in Journal of Computer Science.
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset blood_transfusion_service_center = fetch_ucirepo(id=176) # data (as pandas dataframes) X = blood_transfusion_service_center.data.features y = blood_transfusion_service_center.data.targets # metadata print(blood_transfusion_service_center.metadata) # variable information print(blood_transfusion_service_center.variables)
Yeh, I. (2008). Blood Transfusion Service Center [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5GS39.
Creators
I-Cheng Yeh
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.