Python Machine Learning Cookbook - Second Edition

How it works...

In this recipe, we have faced a clustering problem by using the mean shift algorithm. It is a clustering type that assigns datapoints to clusters in an iterative manner by moving points to the mode. The mode is the value that appears most frequently.

The algorithm assigns iteratively each data point to the centroid of the nearest cluster. The centroid of the nearest cluster is determined by where most of the neighboring points are located. Thus, at each iteration, each data point approaches the point where the greatest number of points is located, which is, or will lead to, the cluster center. When the algorithm stops, each point is assigned to a cluster. Unlike the k-means algorithm, the mean shift algorithm is not required ...