K-medians

The K-medians algorithm is similar to K-means, but it characterizes the center of each cluster in terms of the median of the items it contains rather than their mean.

K-medians is a clustering algorithm used in applications like logistics where the vector space is a geographical map. It works by iteratively assigning each data point to the nearest cluster center and then updating the cluster centers to be the median of the points in the cluster. This process continues until the cluster assignments no longer change.

For example, in a logistics application, each data point could represent a delivery location, and the cluster centers could represent distribution centers. By using the median rather than the mean, K-medians is less sensitive to outliers, making it more robust for certain applications.

In summary, K-medians is a clustering algorithm that uses the median to define cluster centers, making it useful for applications where robustness to outliers is important.