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Efficient Classification Technique on Healthcare Data

  • Rella Usha RaniEmail author
  • Jagadeesh Kakarla
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 713)

Abstract

In theprocess of improvisation of classification accuracy rate, many classifiers are made pass through this framework of classification and prediction. The proposed best classifier isthe random forest classifier based on various parameters. The kidney disease diagnosis is done based on the available machine learning classifiers and presented an effective classifier with great accuracy rate of prediction. In the proceedings of ayush to kidney (AtoK) kidney disease diagnose intelligence model, this paper is reporting the best classifier in development of prediction model.

Keywords

Classifier Accuracy Kidney Machine learning 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of CSECVR College of EngineeringHyderabadIndia
  2. 2.Department of CSCentral University of RajasthanAjmerIndia

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