{"id":27198743,"url":"https://github.com/mdparwez/onlinepaymentfraud","last_synced_at":"2026-05-07T00:32:24.852Z","repository":{"id":239129188,"uuid":"798627377","full_name":"MdParwez/onlinepaymentfraud","owner":"MdParwez","description":"online payment fraud  using machine learning ","archived":false,"fork":false,"pushed_at":"2024-06-03T04:00:14.000Z","size":2450,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-09T20:55:31.401Z","etag":null,"topics":["machine-learning-algorithms","python","streamlit"],"latest_commit_sha":null,"homepage":"https://tejasjd08-final-online-payment-fraud-detection.streamlit.app/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MdParwez.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-10T06:45:12.000Z","updated_at":"2024-06-03T04:00:17.000Z","dependencies_parsed_at":null,"dependency_job_id":"22723c7b-62ca-4cd0-b8b2-f9c2092d1471","html_url":"https://github.com/MdParwez/onlinepaymentfraud","commit_stats":null,"previous_names":["mdparwez/onlinepaymentfraud"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MdParwez%2Fonlinepaymentfraud","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MdParwez%2Fonlinepaymentfraud/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MdParwez%2Fonlinepaymentfraud/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MdParwez%2Fonlinepaymentfraud/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MdParwez","download_url":"https://codeload.github.com/MdParwez/onlinepaymentfraud/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248111971,"owners_count":21049577,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["machine-learning-algorithms","python","streamlit"],"created_at":"2025-04-09T20:55:34.645Z","updated_at":"2026-05-07T00:32:24.815Z","avatar_url":"https://github.com/MdParwez.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ONLINE-PAYMENT-FRAUD-DETECTION  (Data Science Project)\n\n### Overview:\n\nThis project focuses on detecting online payment fraud using various machine learning algorithms. The objective is to identify fraudulent transactions to enhance the security of online payment systems.\n\n### Machine Learning Algorithms Used\n\n- **Support Vector Machine (SVM)**: Employed to classify transactions as fraudulent or non-fraudulent based on feature analysis.\n- **K-Nearest Neighbors (KNN)**: Used for classification by finding the majority class among the k-nearest transactions.\n- **Random Forest**: Utilized for its ensemble learning method, leveraging multiple decision trees to improve prediction accuracy.\n- **Logistic Regression**: Applied for binary classification to estimate the probability of a transaction being fraudulent.\n\n### Project Workflow\n\n1. **Data Collection and Preprocessing**:\n   - Gathered a dataset containing transaction details.\n   - Cleaned and preprocessed the data to handle missing values and categorical features.\n   - Performed feature scaling to standardize the dataset.\n\n2. **Exploratory Data Analysis (EDA)**:\n   - Conducted EDA to understand the distribution of data.\n   - Visualized patterns and correlations between different features.\n   - Identified key indicators of fraudulent transactions.\n\n3. **Model Training and Evaluation**:\n   - Split the dataset into training and testing sets.\n   - Trained each machine learning algorithm on the training data.\n   - Evaluated the models using metrics such as accuracy, precision, recall, and F1-score.\n   - Compared the performance of different algorithms to select the best model.\n\n4. **Deployment**:\n   - Integrated the best-performing model into a Streamlit application.\n   - Created an interactive user interface for real-time fraud detection.\n   - Deployed the application to provide a user-friendly platform for detecting fraudulent transactions.\n\n### Streamlit Application\n\nThe final model was deployed using Streamlit, a powerful and easy-to-use framework for building data applications. The Streamlit app allows users to:\n\n- Upload transaction data for analysis.\n- View predictions on whether a transaction is fraudulent or not.\n- Access visualizations and insights derived from the data.\n\n### Conclusion\n\nThis project demonstrates the effectiveness of machine learning algorithms in detecting online payment fraud. By leveraging multiple algorithms and deploying the solution on a Streamlit app, it provides a robust and user-friendly tool for enhancing the security of online payment systems.\n\n### Future Work\n\n- **Improving Model Accuracy**: Explore additional machine learning algorithms and techniques to further improve prediction accuracy.\n- **Real-time Detection**: Implement real-time data processing and fraud detection capabilities.\n- **Scalability**: Enhance the application to handle larger datasets and more complex transaction patterns.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmdparwez%2Fonlinepaymentfraud","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmdparwez%2Fonlinepaymentfraud","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmdparwez%2Fonlinepaymentfraud/lists"}