A model for forecasting dengue disease using genetic based weighted FP-growth
Vandana Rajput, Amit Kumar Manjhvar · 2017 International Conference on Trends in Electronics and Informatics (ICEI) · 2017
In few years, Data Mining is a big and motivating research area in medical & healthcare department. It is helpful to find profitable and successful systematic method in wellbeing data. It is helpful to forecast the different diseases like-Dengue fever, Cancer, Diabetes, heart disease etc. A big agreement of reading former conceded out on disease detection using an optimization technique to palliate the drawbacks of conventional approaches. In our paper, we have to design a novel model for forecast the dengue disease. Here, we use genetic algorithm to calculate the actual weight of attributes afterwards applied the FP-Growth with actual weight. Theoretical study and experiments have displayed that the modified approach is able to detect the virtual significance of attributes in requisites of their weights. This model are deliberate and the parameters are set to get optimal forcast performance. At last, the outcome displays that the model produces the better prediction.