IDENTIFICATION AND CLASSIFICATION OF FOODBORNE DISEASE OUTBREAKS

Abstract

Foodborne disease is commonly caused by consuming contaminated food and beverages so the identification and classification of foodborne disease outbreaks is necessary to prevent and reduce the risk of illness and death. The purpose of this research is to identify the causative agents of disease as soon as possible to improve the food safety to prevent from illnesses and deaths. The useful patterns have been identified with analysis on dataset and also determine the large number of outbreaks occurs in year, food, location and species. The classification is done in Decision Tree, Naïve Bayes and Random Forest classifiers. The experiments on the dataset have proven the efficiency of purposed approach for identification and classification of outbreak patterns.