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Diabetes-Predection-using-Ensemble-Learning

sumaaan / Diabetes-Predection-using-Ensemble-Learning

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This research work summarized different machine learning algorithms to create models for predicting diabetes patients utilizing the Diabetes Dataset (PIDD) from the UCI repository. The classifiers were K-Nearest Neighbors, Naïve Bayes, Support Vector, Decision Tree, Random Forest, Logistic Regression and Ensemble Model using a voting classifier.

machine-learning random-forest svm naive-bayes-classifier ensemble-learning logistic-regression confusion-matrix decision-trees feature-engineering knn boxplot datavisualization voting-classifier roc-score streamlit-webapp confusion-matrix-heatmap auc-score handling-outlier
  • Updated Jan 8, 2023
  • Jupyter Notebook

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