Fuzzy association rule mining and classification for the prediction of malaria in South Korea
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منابع مشابه
Fuzzy association rule mining and classification for the prediction of malaria in South Korea
BACKGROUND Malaria is the world's most prevalent vector-borne disease. Accurate prediction of malaria outbreaks may lead to public health interventions that mitigate disease morbidity and mortality. METHODS We describe an application of a method for creating prediction models utilizing Fuzzy Association Rule Mining to extract relationships between epidemiological, meteorological, climatic, an...
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15 صفحه اولFuzzy association rule mining approaches for enhancing prediction performance
This paper presents an investigation into two fuzzy association rule mining models for enhancing prediction performance. The first model (the FCM-Apriori model) integrates Fuzzy C-Means (FCM) and the Apriori approach for road traffic performance prediction. FCM is used to define the membership functions of fuzzy sets and the Apriori approach is employed to identify the Fuzzy Association Rules (...
متن کاملFuzzy Association Rule Mining
Corresponding Author: Lekha. A., Research Scholar, Dr M G R Educational Research Institute, Chennai, India-600095, Assistant Professor, Department of MCA, PESIT, Bangalore Email: [email protected] Abstract: The paper attempts to propose a fuzzy logic association algorithm to predict the risks involved in identifying diseases like breast cancer. Fuzzy logic algorithm is used to find associatio...
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ژورنال
عنوان ژورنال: BMC Medical Informatics and Decision Making
سال: 2015
ISSN: 1472-6947
DOI: 10.1186/s12911-015-0170-6