Abstract
his study aimed to develop a prediction model for the elderly with the limitation of ADL in Korea using data mining of large cross sectional data set. We used the large data set of 2008 Korean Elderly Survey(KES) which was consisted of 15,146 elderly data. Target variable was limitation of ADL and input variables were demographic, health related and socioeconomic characteristics of the Korean elderly population. SPSS Clementine 12.0 program was used to develop a prediction model. Feature selection node was used to select important variables and C&R tree showed the best prediction with the accuracy of 80.82% among C5.0, C&R Tree, QUEST, and CHAID model. In C&R tree modeling, high risk group of MMSE score, using wheelchair or taxi as transportation, illiteracy, very poor health condition, one or more handicap, and low physical activity explained the best the characteristics of the elderly with ADL limitation.
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2010-0024922).
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Park, M., Kim, S. (2012). A Decision Tree Model to Analyze the Characteristics of the Elderly with ADL Limitation Using Data Mining. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_64
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DOI: https://doi.org/10.1007/978-3-642-32645-5_64
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