Clustering Analysis and 3D Visualization Dashboard

A dashboard for analyzing datasets by using K-means and Hierarchical clustering algorithms. This tool helps determine the optimal number of clusters and provides detailed 3d visualizations and comparisons of clustering results.

🎯Click here and Try it out
(plz get it back up and wait it waking up for a moment)

Project Details

Here’s more detailed information about it:

• Multiple Data Sources: Analyze built-in sample datasets or upload your own CSV files
• Custom Dataset Mapping: For uploaded files, map columns to appropriate features
  
• Interactive 3D Visualizations: Compare original data with K-means and Hierarchical clustering results
• Optimal Cluster Detection: Automated determination of the optimal number of clusters using:
  • Elbow Method
  • Silhouette Score
  • Calinski-Harabasz Method
  • Ensemble approach combining all methods
    
• Comprehensive Performance Metrics:
  • Precision, Recall, Jaccard Index
  • Rand Index
  • Fowlkes-Mallows Score
    

Technology Stack

• Python
• Streamlit
• Pandas
• NumPy
• Plotly
• Scikit-learn
• SciPy
• kneed

• Repository