Abstract
Data mining have been used in real time applications due to its artificial intelligence nature. Data mining is highly used in medical domain as it helps in making better predictions and supports in decision making. It also supports physicians in developing better diagnostic treatments. We have used Data mining to analyze Zika virus disease which leads to many deaths in South Africa and America. Zika virus is very fatal and spreads due to virus transmitted primarily by Aedes Mosquito. In this research work we have worked on tree based mining algorithms and further improvement is done by using filters which removes noise from the dataset. In this we worked on J48, decision tree, SVM and Random forest algorithms and indicate Experimental results.
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Uma Mahesh, J., Srinivas Reddy, P., Sainath, N., Vijay Kumar, G. (2017). Evaluating the Performance of Tree Based Classifiers Using Zika Virus Dataset. In: Saini, H., Sayal, R., Rawat, S. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 8. Springer, Singapore. https://doi.org/10.1007/978-981-10-3818-1_7
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