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Research work on Diabetes Prediction using Machine Learning

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ShubhanshuTripathi/Diabetes-Prediction

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This is part of my M.Tech. Thesis work. Main highlights are:

  • Achieved up to 81.6% accuracy in Diabetes Prediction on Pima Indians Diabetes Database with Random Forest classifier
  • Applied and analysed accuracies of “K-Nearest Neighbors, Support Vector Machine, Decision Tree and Random Forest” classification algorithms for diabetes prediction
  • Achieved up to 7.04% improvement in the accuracy of Decision Tree classification algorithm for Diabetes Prediction
  • Predicted missing values present in the dataset using a set of “Linear Regression, Support Vector Regression, Decision Tree and Random Forest” regression algorithms
  • Performed Dataset Balancing using SMOTE algorithm and then Feature Scaling