Comparative Study of Machine Learning Techniques to Predict Diabetic Retinopathy Using WEKA Tool

Comparative Study of Machine Learning Techniques to Predict Diabetic Retinopathy Using WEKA Tool

Authors

  • Ms. Merin Manoj ktu
  • Ahil Sandes

Keywords:

Machine Learning, Diabetic Retinopathy, Random Forest, J48, OneR, Weka, Accuracy

Abstract

—Diabetic Retinopathy (DR) is the maximum not
unusual reason of newly identified blindness every 12
months. Annual eye checking for diabetic patients are
cautioned so that it will locate and treat DR in a well-timed
way, thinking about that blindness from this circumstance
is preventable with early detection. DR detectionis purely
based totally on gift affected character information. Now an
afternoon’s scientific information growing specially and we
need to specify that information for detection. However it's
time ingesting as a result records mining techniques
facilitates to get rid from this issue. This paper compares the
output of various machine learning techniques like Random
Forest, OneR and J48 on diabetic retinopathy dataset in
order to determine which algorithm is best for predicting
diabetic retinopathy correctly

Published

2022-12-20

How to Cite

Ms. Merin Manoj, & Ahil Sandes. (2022). Comparative Study of Machine Learning Techniques to Predict Diabetic Retinopathy Using WEKA Tool. National Conference on Emerging Computer Applications, 3(1). Retrieved from https://ajcejournal.in/nceca/article/view/72

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