Clustering Explorer App is an interactive web application that demonstrates K-means clustering algorithm through real-time visualization. It provides an intuitive way to understand how data points are grouped into clusters based on their similarities.

Features
○ Interactive 2D visualization of K-means clustering.
○ Real-time animation of cluster formation.
○ Adjustable number of clusters (K) from 2 to 10.
○ Smooth point movement with physics-based animation.
○ Maximum 10 iterations for quick convergence.
○ Physics-based point movement with velocity and damping.

Algorithm
○ Random initialization of centroids.
○ Point-to-cluster assignment based on Euclidean distance.
○ Centroid position updates based on cluster means.

Click on the picture to go to the app.

This tool helps users in understanding how K-means clustering operates, the impact of different K values, the process of cluster formation and convergence, and the iterative nature of clustering algorithms. It is valuable for educational demonstrations, data science learning, algorithm visualization, and interactive presentations.