A project that explores clustering food products based on nutritional attributes using K-Means, Fuzzy C-Means, and DBSCAN algorithms, with a Streamlit dashboard for visualizing results.
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Updated
Aug 11, 2024 - Jupyter Notebook
A project that explores clustering food products based on nutritional attributes using K-Means, Fuzzy C-Means, and DBSCAN algorithms, with a Streamlit dashboard for visualizing results.
This is the third project for the course Inteligent Systems (IF684) in CIN-UFPE. This project objective is use clustering to analyze the data of wholesale customers, which is data about a wholesale distributor.
Simple implementation of Fuzzy C-means algorithm using python. It is used for soft clustering purpose. Visualizing the algorithm step by step with the cluster plots at each step and also the final clusters.
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