Mosquito Borne Disease Incidence Prediction System using Fuzzy Weighted Associative Classification

Recently, applications attracted rampant attention in Epidemiology, Medical Entomology, Bio informatics, and Bio surveillance. Data mining applications is greatly useful to all stake holders in the healthcare industry. Associative Classification (AC) is a branch of data mining, a larger area of scientific study. To build a model for the purpose of prediction, AC is a suitable prediction technique, which integrates two data mining tasks, association rule mining and classification. The main aim of classification is the prediction of class labels, while association rule discovery describes relationship between items in a transactional database. Of late, Associative Classifier is having better accuracy as compared to that of traditional classifiers. Mosquito Borne Diseases that place a heavy burden on public health system on most of the tropical countries around the world. There is a need to develop prediction methods to augment existing control strategies. In this paper we use Fuzzy Weighted Associative Classifier to build an effective prediction model to predict mosquito borne disease incidence