Diabetes-Prediction-using-machine-learning

The project used machine learning classifiers to compare and analyze accuracy of different machine learning classifier models.
The proposed method uses Logistic Regression, KNN, Naive Bayes, SVM, Decision Tree and Random Forest classifiers.
The result shows that the Random Forest achieved highest accuracy of 81.506.
The proposed machine learning model is deployed into a webpage using streamlit in python

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
Diabetes_Prediction_using_different_Machine_Learning_Classifiers.pdf		Diabetes_Prediction_using_different_Machine_Learning_Classifiers.pdf
README.md		README.md
app.py		app.py
code.ipynb		code.ipynb
diabetes.csv		diabetes.csv
model.sav		model.sav
webInterface.png		webInterface.png

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