This project provides a simple web-based interface for performing K-Medoids clustering analysis on a dataset. It allows users to upload a CSV file, specify the number of clusters, and visualize the clustering results.
- Clone the repository:
git clone https://github.com/IRims/streamlit_Kmediod.git
- Install the required dependencies:
pip install -r requirements.txt
-
Run the Streamlit app:
python -m streamlit run main.py
-
Upload a CSV file containing the dataset you want to analyze.
-
Specify the number of clusters.
-
Explore the clustering results using various visualizations and summary statistics.
main.py: Contains the Streamlit web application code.model.py: Contains functions for loading the dataset, performing K-Medoids clustering, and visualizing clustering results.requirements.txt: Lists the required Python packages and their versions.
- Rimsha Zahid (https://github.com/IRims)
