k-means object clustering

This is a 2D object clustering with k-means algorithm.

Code Link

Mapping.kmeans_clustering.kmeans_clustering.kmeans_clustering(rx, ry, nc)

Performs k-means clustering on the given dataset, iteratively adjusting cluster centroids until convergence within a defined threshold or reaching the maximum number of iterations.

The implementation initializes clusters, calculates initial centroids, and refines the clusters through iterative updates to optimize the cost function based on minimum distance between datapoints and centroids.

Parameters:

• rx – List[float] The x-coordinates of the dataset points to be clustered.

• ry – List[float] The y-coordinates of the dataset points to be clustered.

• nc – int The number of clusters to group the data into.

Returns:

Clusters

An instance containing the final cluster assignments and centroids after convergence.

Raises:

None –