This is a machine learning work that uses various machine learning algorithms to predict whether a patient is diabetic or not (non-diabetic). Here, various type of machine learning algorithms like Support Vector Machine Classifier (SVM), Random Forest Classifier (RF), Decision Tree Classifier (DT), K-Nearest Neighbours (KNN), Logistic Regression (LR), Logistic Regression (LR) with Cross-Validation (CV), Naive Bayes Classifier (NB), and XGBoost Classifier (XGB) are used for this.
Logistic Regression gives 83.62% testing accuracy which is the best testing accuracy among other machine learning models
Dataset is present in Kaggle
Link: https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database?resource=download
Link: https://diabetes-prediction-of-females-using-machine-learning-web-app.streamlit.app