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Evaluating the Performance of Tree Based Classifiers Using Zika Virus Dataset

  • J. Uma MaheshEmail author
  • P. Srinivas Reddy
  • N. Sainath
  • G. Vijay Kumar
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 8)

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.

Keywords

Data mining Classification Tree based classifier WEKA Zika virus dataset Decision tree 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • J. Uma Mahesh
    • 1
    Email author
  • P. Srinivas Reddy
    • 2
  • N. Sainath
    • 2
  • G. Vijay Kumar
    • 3
  1. 1.Department of Computer Science & EngineeringGeethanjali College of Engineering & TechnologyHyderabadIndia
  2. 2.CSEBharat Institute of Engineering & TechnologyHyderabadIndia
  3. 3.ECMK L UniversityGunturIndia

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