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International Conference on Intelligent Human Computer Interaction

IHCI 2019: Intelligent Human Computer Interaction pp 175–188Cite as

Rule Generation of Cataract Patient Data Using Random Forest Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11886))

Abstract

Cataract is one of the common problems among the humans. Cataract is the condition caused due to clouding of lens in the eye which eventually may lead to blindness. In last few years, data mining has been widely used to build the predictive model in various fields. In this paper, historical data of cataract patient has been used to build the predictive model. Random forest algorithm is one of the decision tree algorithms for predictive modeling. Random forest algorithm incorporates advantages of classification and regression. Present study uses random forest method to create a model for prediction of cataract. The random forest algorithm is also tested for Out of Bag estimation error.

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Author information

Authors and Affiliations

  1. MATS University, Raipur, India

    Mamta Santosh Nair

  2. MSIT, MATS University, Raipur, India

    Umesh Kumar Pandey

Authors
  1. Mamta Santosh Nair
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  2. Umesh Kumar Pandey
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Corresponding authors

Correspondence to Mamta Santosh Nair or Umesh Kumar Pandey .

Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology, Allahabad, India

    Uma Shanker Tiwary

  2. Indian Institute of Technology, Jodhpur, India

    Santanu Chaudhury

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Nair, M.S., Pandey, U.K. (2020). Rule Generation of Cataract Patient Data Using Random Forest Algorithm. In: Tiwary, U., Chaudhury, S. (eds) Intelligent Human Computer Interaction. IHCI 2019. Lecture Notes in Computer Science(), vol 11886. Springer, Cham. https://doi.org/10.1007/978-3-030-44689-5_16

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  • DOI: https://doi.org/10.1007/978-3-030-44689-5_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-44688-8

  • Online ISBN: 978-3-030-44689-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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