ICFICE 2018
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
Epidemic Respiratory Disease Prediction Using Ensemble Method |
¿µ¹®Á¦¸ñ(English Title) |
Epidemic Respiratory Disease Prediction Using Ensemble Method |
ÀúÀÚ(Author) |
Su-Jin Seong
Seong-Jae Park
Tae-Ho Park
Chang-Uk Shin
Da-Sol Park
Jeong-MooKim
Jeong-Won Cha
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¿ø¹®¼ö·Ïó(Citation) |
VOL 10 NO. 01 PP. 0253 ~ 0256 (2018. 06) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
The purpose of this paper is to construct a model for estimating occurrence of respiratory diseases using weather and air pollution data. We collect the data for one year. We use a Linear Support Vector Machine (SVM), Random Forest, Deep Neural Network (DNN), Ensemble modeling technique. As a result, the ensemble model has the highest performance (F1-Score: 0.7328, AUC: 0.7273). From these results, we found that improving the atmospheric environment has a significant impact on improving people's health.
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Å°¿öµå(Keyword) |
respiratory diseases
SVM
Random forest
DNN
Ensemble
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