## Clustering / K-means - estimate K

### Description

This tool estimates the number of cluster to be used in the K-means clustering

### Parameters

- Image width (200-3200) [600]
- Image height (200-3200) [600]

### Details

A K-means clustering is performed for every value of K between 1 and 100. When the
change in the within sum of squares of the clustering is less than 1% compared to the
previous number of K, the analysis is terminated.

The resulting image plots the K against the within sum of squares. A suitable number
of K can be estimated from this image. Search for the point, where the curve has a shoulder,
and pick the number of K from that region. For example, in the image below, a suitable
K could be somewhere between 7 and 13.

This clustering is done using Euclidean distance, and cannot be changed.

### Output

A PNG image that can be visualized in the Chipster GUI.