Application of CART Algorithm in Blood Donors Classification
T. Santhanam and Shyam Sundaram
DOI : 10.3844/jcssp.2010.548.552
Journal of Computer Science
Volume 6, Issue 5
Problem statement: This study used data mining modeling techniques to examine the blood donor classification. The availability of blood in blood banks is a critical and important aspect in a healthcare system. Blood banks (in the developing countries context) are typically based on a healthy person voluntarily donating blood and is used for transfusions or made into medications. The ability to identify regular blood donors will enable blood banks and voluntary organizations to plan systematically for organizing blood donation camps in an effective manner. Approach: Identify the blood donation behavior using the classification algorithms of data mining. The analysis had been carried out using a standard blood transfusion dataset and using the CART decision tree algorithm implemented in Weka. Results: Numerical experimental results on the UCI ML blood transfusion data with the enhancements helped to identify donor classification. Conclusion: The CART derived model along with the extended definition for identifying regular voluntary donors provided a good classification accuracy based model.
© 2010 T. Santhanam and Shyam Sundaram. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.