{"id":28551941,"url":"https://github.com/philiptitus/mall-customers","last_synced_at":"2025-07-03T17:30:48.482Z","repository":{"id":296444413,"uuid":"946585466","full_name":"philiptitus/Mall-Customers","owner":"philiptitus","description":"K-means Model to categorize Mall customers into different clusters based on their spending habits ","archived":false,"fork":false,"pushed_at":"2025-05-30T18:46:35.000Z","size":145,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-10T04:07:42.742Z","etag":null,"topics":["clustering","k-means-clustering","sickit-learn","silhouette-score","unsupervised-clustering","unsupervised-learning","unsupervised-machine-learning"],"latest_commit_sha":null,"homepage":"https://philiptitus-mall-customers-app-8gflbs.streamlit.app/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/philiptitus.png","metadata":{"files":{"readme":"readme.md","changelog":null,"contributing":null,"funding":null,"license":null,"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,"zenodo":null}},"created_at":"2025-03-11T11:20:07.000Z","updated_at":"2025-05-30T18:51:19.000Z","dependencies_parsed_at":"2025-05-31T03:31:26.404Z","dependency_job_id":"bbb3bf61-24bc-478a-8c67-453a95612c32","html_url":"https://github.com/philiptitus/Mall-Customers","commit_stats":null,"previous_names":["philiptitus/mall-customers"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/philiptitus/Mall-Customers","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/philiptitus%2FMall-Customers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/philiptitus%2FMall-Customers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/philiptitus%2FMall-Customers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/philiptitus%2FMall-Customers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/philiptitus","download_url":"https://codeload.github.com/philiptitus/Mall-Customers/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/philiptitus%2FMall-Customers/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263369435,"owners_count":23456300,"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":["clustering","k-means-clustering","sickit-learn","silhouette-score","unsupervised-clustering","unsupervised-learning","unsupervised-machine-learning"],"created_at":"2025-06-10T04:07:42.551Z","updated_at":"2025-07-03T17:30:48.477Z","avatar_url":"https://github.com/philiptitus.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Mall Customers K-Means Clustering Model\n\nThis project implements K-Means clustering on the \"Mall Customers\" dataset from Kaggle. The goal is to segment customers based on their annual income and spending score.\n\n## Project Structure\n\n- `model.ipynb`: Jupyter Notebook containing the implementation of the K-Means clustering model.\n- `mall.csv`: Dataset used for clustering.\n- `README.md`: Project documentation.\n- `requirements.txt`: List of dependencies required to run the project.\n\n## Dataset\n\nThe dataset used in this project is the \"Mall Customers\" dataset from Kaggle. It contains information about customers, including their annual income and spending score.\n\n## Steps\n\n1. **Load the Dataset**: Load the dataset using pandas and display the first few rows.\n2. **Data Preprocessing**: Check for missing values and select relevant features for clustering.\n3. **Standardize the Data**: Standardize the features to ensure equal contribution to distance calculations.\n4. **Implement K-Means Clustering**: Initialize and fit the K-Means model, then predict the cluster for each data point.\n5. **Visualize the Clusters**: Create a scatter plot to visualize the clusters.\n6. **Evaluate Clustering**: Use the Elbow Method and Silhouette Method to determine the optimal number of clusters.\n7. **Save the Model and Clustered Data**: Save the K-Means model and the clustered data to files.\n\n## Evaluation\n\nThe performance of the K-Means clustering model is evaluated using the silhouette score. A higher silhouette score indicates better-defined clusters.\n\n\n## Improving the Model\n\nTo improve the performance of the K-Means clustering model, consider the following strategies:\n\n- Feature scaling and normalization\n- Dimensionality reduction (e.g., PCA)\n- Optimal number of clusters (Elbow Method, Silhouette Method)\n- Initialization (k-means++)\n- Multiple runs (n_init parameter)\n- Alternative clustering algorithms (e.g., GMM, DBSCAN)\n- Incorporate domain knowledge\n\n## Installation\n\nTo run this project, you need to have Python installed. You can install the required dependencies using the following command:\n\n```sh\npip install -r requirements.txt\n```\n\n## Usage\n\nOpen the `model.ipynb` file in Jupyter Notebook or JupyterLab to see the implementation and results of the K-Means clustering model.\n\n## License\n\nThis project is licensed under the MIT License.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fphiliptitus%2Fmall-customers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fphiliptitus%2Fmall-customers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fphiliptitus%2Fmall-customers/lists"}