Dengue Prediction Using Hierarchical Clustering Methods

  • S. Vandhana
  • J. Anuradha
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10844)


The occurrence of dengue is rapidly increasing in every year. Considering the welfare of the public, it is essential to have detailed study on the affected areas of dengue and its intensity for the control of disease. This paper uses hierarchical clustering technique to classify the data of dengue cases reported and deaths occurred in various states of India. An agglomerative clustering of ward method is used for clustering. The outcomes are represented in Indian map using shape file with RStudio. The data is predicted for 2018, by logarithmic transformation using linear models of regression. K-Nearest Neighbour algorithm is used for predicting the cluster data for 2018. The results have shown that the frequency of dengue happening or the intensity is considerably reduced in many states.


Clustering Prediction Hierarchical clustering Linear model K-Nearest Neighbour (KNN) 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Vellore Institute of TechnologyVelloreIndia

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