K-Means Clustering - etak64n.dev

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Algorithm

K clusters 3

Epsilon 50

MinPts 3

Initialization

Speed 5

Dataset

Points 120

Options

Voronoi regions

Centroid trails

Controls

Points: 0 Iter: 0 WCSS: — Status: —

Converged!

Elbow Method

WCSS vs K — look for the "elbow" to find optimal K

K-Means Clustering

1Choose an algorithm and dataset from the panel (⚙ top-right)
2Click Generate Dataset or click the canvas to add points manually
3Hit Step to advance one step, or Play to animate automatically
4Watch centroids move and clusters form; Voronoi boundaries show regions
5Use Elbow Method Chart to find the optimal K

Click anywhere to dismiss