https://github.com/ankushmallick1100/diabetes-prediction-of-females-using-maching-learning-techniques
This is a machine learning work that uses various machine learning algorithms to predict whether a patient is diabetic or not. Here various machine learning algorithms like SVM, RF Classifier, DT Classifier, KNN, LR , LR with CV, NB Classifier, and XGB are used. For this work, a website is made with Python Streamlit library.
https://github.com/ankushmallick1100/diabetes-prediction-of-females-using-maching-learning-techniques
classification cross-validation decision-tree-classifier diabetes diabetes-prediction jupyter jupyter-notebook logistic-regression machine-learning machine-learning-algorithms numpy pandas python random-forest random-forest-classifier regression streamlit support-vector-machine xgboost xgboost-classifier
Last synced: 16 days ago
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This is a machine learning work that uses various machine learning algorithms to predict whether a patient is diabetic or not. Here various machine learning algorithms like SVM, RF Classifier, DT Classifier, KNN, LR , LR with CV, NB Classifier, and XGB are used. For this work, a website is made with Python Streamlit library.
- Host: GitHub
- URL: https://github.com/ankushmallick1100/diabetes-prediction-of-females-using-maching-learning-techniques
- Owner: ankushmallick1100
- Created: 2023-01-04T14:08:08.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-03-20T14:47:52.000Z (7 months ago)
- Last Synced: 2025-09-29T19:44:24.898Z (29 days ago)
- Topics: classification, cross-validation, decision-tree-classifier, diabetes, diabetes-prediction, jupyter, jupyter-notebook, logistic-regression, machine-learning, machine-learning-algorithms, numpy, pandas, python, random-forest, random-forest-classifier, regression, streamlit, support-vector-machine, xgboost, xgboost-classifier
- Language: Jupyter Notebook
- Homepage: https://diabetes-prediction-of-females-using-machine-learning-web-app.streamlit.app
- Size: 106 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Diabetes Prediction of Females using Machine Learning Techniques
# Description
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
Dataset is present in Kaggle
Link: https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database?resource=download
# Deployed Web App in public
Link: https://diabetes-prediction-of-females-using-machine-learning-web-app.streamlit.app