Skip to content

This is a machine learning project that uses various machine learning algorithms to predict whether a patient is diabetic or not. Here I am using variour machine learning algorithms like Support Vector Machines(SVM), Random Forest Classifier, Decision Tree Classifier, K-Nearest Neighbours(KNN), Logistic Regression & with Cross Validation(CV) and NB

Notifications You must be signed in to change notification settings

ankushmallick1100/Diabetes-prediction-using-maching-learning

Repository files navigation

Diabetes prediction using Maching Learning

Description

This is a machine learning project that uses various machine learning algorithms to predict whether a patient is diabetic or not. Here I am using variour machine learning algorithms like Support Vector Machines(SVM), Random Forest Classifier, Decision Tree Classifier, K-Nearest Neighbours(KNN), Logistic Regression, Logisitic Regression with Cross Validation(CV), Naive Bias, and XGBoost Classifier. I have wrtten a paper in this topic please check it out. The link of the paper is given below.

Logistic Regression gives the best accuracy

Dataset

Dataset is present in Kaggle
Link: https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database?resource=download

Paper on this topic

Link:

Deployed App in public

Link: https://diabetes-prediction-web-app-ankush-mallick.streamlit.app/

About

This is a machine learning project that uses various machine learning algorithms to predict whether a patient is diabetic or not. Here I am using variour machine learning algorithms like Support Vector Machines(SVM), Random Forest Classifier, Decision Tree Classifier, K-Nearest Neighbours(KNN), Logistic Regression & with Cross Validation(CV) and NB

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published